Data Engineer (AWS + Apache Flink + Java)

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About The Role

AWS, real-time streaming, Apache Flink, and Java

Key Responsibilities

• Real-Time Pipeline Development
• Build and maintain real-time data pipelines using Apache Flink on AWS.
• Develop complex Flink DataStream / SQL applications using Java.
• Implement stateful processing, event-time handling, windows, fault tolerance.
• AWS Data Engineering
• Work with AWS services:
• Kinesis, MSK (Kafka)
• S3, Glue, EMR, Lambda
• Redshift, DynamoDB, Athena
• Optimize cloud infrastructure for cost, scalability, and performance.
• Data Integration & Architecture
• Integrate pipelines with S3, DWs, NoSQL, APIs.
• Ensure data quality, schema evolution, and efficient serialization (Avro/Parquet).
• Contribute to real-time data architecture and ingestion strategies.
• Optimization, Monitoring & Reliability
• Tune Flink jobs for latency, throughput, checkpointing, parallelism.
• Implement monitoring via CloudWatch, Prometheus, Grafana, etc.
• Troubleshoot distributed streaming systems.
• Collaboration & Best Practices
• Work with architects, analysts, ML teams.
• Follow CI/CD, automated testing, IaC (Terraform/CloudFormation).
• Maintain documentation and reusable libraries.
  

Required Skills & Experience

• 3–7+ years as a Data/Streaming Engineer.
• Strong in Java (multithreading, functional programming).
• Mandatory: Hands-on Apache Flink development.
• Proficient with AWS data stack: Kinesis/MSK, S3, Glue, Redshift, EMR, Lambda.
• Solid knowledge of distributed systems, streaming patterns, SQL, data lakes.
• Experience with Git, Jenkins, GitHub Actions, IaC.
  

Good to Have

• Kafka internals.
• Flink Table/SQL API, PyFlink.
• Python scripting.
• Docker, Kubernetes, AWS EKS.
• Observability tools (Datadog, New Relic, OpenTelemetry).
  

Education

Computer Science, Engineering, Information Systems