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We are seeking a Salesforce SDET with hands-on experience in software testing, test automation, Salesforce applications, and API testing. The ideal candidate will have experience testing Salesforce platforms and developing automated test solutions using modern tools and programming languages.

Roles and Responsibilities

• Design, develop, and execute manual and automated test cases for Salesforce applications.
• Perform functional, regression, integration, and API testing.
• Test Salesforce Sales Cloud, Service Cloud, or similar Salesforce platforms.
• Develop and maintain automated test scripts using appropriate testing frameworks.
• Validate REST APIs using tools such as Postman and REST-based testing frameworks.
• Identify, document, and track defects through resolution.
• Collaborate with developers, business analysts, and other stakeholders to ensure application quality.

Qualifications

• 2+ years of experience in software testing or SDET roles.
• Hands-on experience testing Salesforce applications.
• Experience with Salesforce Sales Cloud, Service Cloud, or similar Salesforce platforms.
• Experience with test automation tools and frameworks.
• Proficiency in Java, JavaScript, Python, or a similar programming language.
• Experience with API testing using Postman or REST-based testing frameworks.
• Strong understanding of software testing methodologies and SDLC.

We are seeking a Salesforce SDET with hands-on experience in software testing, test automation, Salesforce applications, and API testing. The ideal candidate will have experience testing Salesforce platforms and developing automated test solutions using modern tools and programming languages.

Roles and Responsibilities

• Design, develop, and execute manual and automated test cases for Salesforce applications.
• Perform functional, regression, integration, and API testing.
• Test Salesforce Sales Cloud, Service Cloud, or similar Salesforce platforms.
• Develop and maintain automated test scripts using appropriate testing frameworks.
• Validate REST APIs using tools such as Postman and REST-based testing frameworks.
• Identify, document, and track defects through resolution.
• Collaborate with developers, business analysts, and other stakeholders to ensure application quality.

Qualifications

• 2+ years of experience in software testing or SDET roles.
• Hands-on experience testing Salesforce applications.
• Experience with Salesforce Sales Cloud, Service Cloud, or similar Salesforce platforms.
• Experience with test automation tools and frameworks.
• Proficiency in Java, JavaScript, Python, or a similar programming language.
• Experience with API testing using Postman or REST-based testing frameworks.
• Strong understanding of software testing methodologies and SDLC.

We are seeking an OT NOC Administrator (Tier 1) to monitor and provide first-level support for critical Operational Technology (OT) environments. The role includes incident response, basic troubleshooting, documentation, and escalation of complex issues.

Primary Responsibilities

• Monitor OT systems, infrastructure, and alerts.
• Respond to alarms and incidents and perform basic troubleshooting.
• Support OT environments, including SCADA, PLCs, and HMIs.
• Follow incident response and escalation procedures.
• Document incidents, resolutions, and operational procedures.
• Assist with patching, performance monitoring, and reporting.
• Collaborate with engineering and technical teams.

Required Qualifications

• Experience in a NOC, Operations Center, or technical support environment.
• Knowledge of OT systems, SCADA, PLCs, and HMIs.
• Experience with monitoring and alerting tools.
• Strong knowledge of TCP/IP, VLANs, routing, and switching.
• Experience with incident monitoring, troubleshooting, and escalation.
• Strong communication and documentation skills.
• Associate degree in a technical field or equivalent experience.
• Ability to work rotating shifts, including nights, weekends, and holidays.

Preferred Qualifications

• OT cybersecurity or industrial control systems experience.
• Windows Server administration experience.
• Experience with system patching and performance monitoring.
• CompTIA Network+, CCNA, or ISA/IEC 62443 certification.

We are seeking an OT NOC Administrator (Tier 1) to monitor and provide first-level support for critical Operational Technology (OT) environments. The role includes incident response, basic troubleshooting, documentation, and escalation of complex issues.

Primary Responsibilities

• Monitor OT systems, infrastructure, and alerts.
• Respond to alarms and incidents and perform basic troubleshooting.
• Support OT environments, including SCADA, PLCs, and HMIs.
• Follow incident response and escalation procedures.
• Document incidents, resolutions, and operational procedures.
• Assist with patching, performance monitoring, and reporting.
• Collaborate with engineering and technical teams.

Required Qualifications

• Experience in a NOC, Operations Center, or technical support environment.
• Knowledge of OT systems, SCADA, PLCs, and HMIs.
• Experience with monitoring and alerting tools.
• Strong knowledge of TCP/IP, VLANs, routing, and switching.
• Experience with incident monitoring, troubleshooting, and escalation.
• Strong communication and documentation skills.
• Associate degree in a technical field or equivalent experience.
• Ability to work rotating shifts, including nights, weekends, and holidays.

Preferred Qualifications

• OT cybersecurity or industrial control systems experience.
• Windows Server administration experience.
• Experience with system patching and performance monitoring.
• CompTIA Network+, CCNA, or ISA/IEC 62443 certification.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.

We are seeking an experienced Kafka/Spark Data Engineer with strong expertise in real-time data processing, streaming technologies, and distributed systems. The role will focus on Kafka, Spark, Redis, Python, and cloud-based Big Data solutions.

Roles and Responsibilities

• Design, develop, and support real-time data streaming and Big Data solutions.
• Develop streaming applications using Apache Kafka, KStreams, and KTables.
• Work with Apache Spark for large-scale data processing.
• Develop applications using Python, Scala, Java, and Bash/Shell scripting.
• Work with NoSQL databases such as Redis, MongoDB, and HBase.
• Design scalable, distributed, and fault-tolerant data architectures.
• Implement data integration, security, and authentication solutions, including Kerberos.
• Work with streaming technologies such as Flink or Storm.
• Support cloud-based data solutions across AWS, Azure, or GCP.
• Apply data analysis, statistical methods, and machine learning techniques where required.
• Create and support data visualizations using Tableau.
• Troubleshoot business-critical applications and provide effective technical solutions.

Required Qualifications

• 9+ years of overall IT/industry experience, with strong Big Data and real-time processing experience.
• Bachelor's or Master's degree in Computer Science, Engineering, Science, or related field.
• Strong hands-on experience with Kafka and real-time streaming.
• Experience with Spark, Redis, and Python.
• Strong understanding of distributed systems, data partitioning, and fault-tolerant architectures.
• Experience with NoSQL databases and cloud platforms.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with Flink, Storm, Scala, or Java.
• Knowledge of machine learning and predictive analytics.
• Experience with Tableau and real-time data visualization.