Technical Stack :

- AWS EMR
- AWS ECS
- Step Functions
- Apache Spark
- PostgreSQL
- DynamoDB
- Glue
- Apache Iceberg

About the Role :

Key Responsibilities :

- Design and implement endtoend data pipelines using Python and Apache Spark, ensuring high performance and reliability.
- Build and maintain scalable data storage solutions such as DynamoDB, Aurora, PostgreSQL, and Redshift, optimizing for low latency and cost efficiency.
- Architect and deploy data lakehouse structures on AWS, leveraging services like S3, Glue, and Athena to enable unified analytics.
- Develop serverless workflows with AWS Step Functions, Lambda, and EventBridge to automate data ingestion, transformation, and orchestration.
- Participate in Agile ceremonies, contribute to sprint planning, and deliver incremental value in short iterations.

Requirements :

- Proficiency in Python and Spark programming.
- Experience building highly scalable, low-latency data systems (e.g., DynamoDB, Aurora, PostgreSQL, Redshift).
- Proven experience designing and implementing data lakehouse architectures on AWS.
- Hands-on experience with AWS services such as Step Functions, Lambda, and EventBridge.
- Experience in Agile development.

📌 Senior Data Engineer - Python/Apache Spark (India)
🏢 ConnectIN Jobs Global
📍 India