Data Engineer - Data Platform (Spark/Kafka/Flink/Scala/Java)

• Join a team building next-generation, cloud-native data platforms powering real-time and batch data movement at enterprise scale.
• You will design and develop streaming and batch frameworks, Kafka/Flink/Spark-based processing engines, and cloud-native solutions on Azure and Kubernetes.
• Ideal candidates have strong distributed systems experience and a passion for platform engineering, automation, and data modernization.

Day to Day Job Duties: (What this person will do on a daily/weekly basis)

• Design, develop, and support scalable real-time and batch data pipelines using Apache Spark, Apache Flink, Apache Kafka, and Airflow.
• Build and enhance metadata-driven self-service data integration platforms and reusable connectors.
• Develop and maintain source and target connectors for relational databases, file systems, Kafka, Cassandra, YugabyteDB, and other enterprise data stores.
• Design, deploy, and operate Kubernetes-based streaming and batch processing platforms.
• Lead cloud migration initiatives from on-premise environments to Microsoft Azure.
• Drive performance tuning, scalability optimization, reliability improvements, and operational excellence across large-scale data workloads.
• Develop cloud-native solutions supporting enterprise data movement and processing.
• Collaborate with product owners, architects, cloud engineering teams, and business stakeholders to deliver enterprise-scale data solutions.
• Contribute to platform modernization, automation, CI/CD implementation, and engineering best practices.
• Support troubleshooting, production stability, and continuous improvement initiatives for critical data platforms.

Basic Qualifications: (What are the skills required for this job with minimum years of experience on each)

• Minimum 8+ years of overall Software Engineering or Data Engineering experience.
• Minimum 5+ years of hands-on experience with Apache Spark for large-scale batch and streaming data processing.
• Minimum 5+ years of hands-on experience with Apache Kafka including event-driven architectures and real-time data streaming solutions.
• Minimum 3+ years of hands-on experience with Apache Flink for stream processing and real-time analytics workloads.
• Minimum 5+ years of experience developing applications using Java and/or Scala.
• Minimum 5+ years of experience writing complex SQL queries and optimizing database performance.
• Minimum 3+ years of experience with Kubernetes and containerized application deployment.
• Minimum 3+ years of experience designing and implementing solutions on Microsoft Azure Cloud.
• Minimum 3+ years of experience building and supporting distributed data platforms using Cassandra, YugabyteDB, PostgreSQL, or similar databases.
• Minimum 3+ years of experience building event-driven architectures and streaming applications.
• Minimum 2+ years of experience implementing CI/CD pipelines, source control, and deployment automation using GitLab, GitHub, or similar tools.
• Minimum 2+ years of experience with cloud-native deployment patterns, containerization, and platform automation.
• Demonstrated experience in performance tuning, troubleshooting, and supporting mission-critical data platforms.

Nice to Have (But Not a Must)

• Experience with Apache Airflow orchestration.
• Experience with metadata-driven data platforms and self-service ingestion frameworks.
• Experience with enterprise cloud migration and modernization programs.
• Experience with platform engineering and internal developer platforms.
• Experience leading technical initiatives, mentoring engineers, or serving as a technical lead.
• Knowledge of DevSecOps, infrastructure as code, and observability frameworks.

Travel: Minimal travel required. Travel may be necessary based on project and stakeholder requirements. Degree: Bachelor’s degree in Computer Science, Information Technology, Engineering, or equivalent work experience.

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