Design, build and optimize ETL pipelines and cloud data workflows using Python, PySpark, AWS Glue and Lambda. Implement data models and schemas in PL/SQL/PostgreSQL, integrate AWS services (SNS, Step Functions), and troubleshoot pipelines for performance, scalability and reliability.
Location: Bangalore
Experience: 6 - 9 Years
We are looking for a Data Engineer with strong expertise in Python, PySpark, AWS Glue, and Lambda. The ideal candidate should have experience in data processing, transformation, and cloud-based data workflows. A strong foundation in PL/SQL and PostgreSQL is required, and experience with AWS services such as SNS and Step Functions, along with Java API development, would be a plus.
Key Responsibilities:- Develop and optimize ETL pipelines using AWS Glue, Lambda, and PySpark.
- Work with large-scale data processing and transformation using Python and Spark.
- Design and implement data workflows for structured and unstructured data.
- Optimize queries and data storage for performance and cost efficiency.
- Develop and maintain data models, schemas, and database structures using PL/SQL and PostgreSQL.
- Integrate AWS services such as SNS, Step Functions, and other cloud-based workflows.
- Collaborate with cross-functional teams to support business data needs.
- Troubleshoot and optimize data pipelines for scalability and reliability.
✅ Python & PySpark – Strong hands-on experience
✅ AWS Glue & Lambda – Experience in serverless data processing
✅ PL/SQL & PostgreSQL – Basic database development and querying skills
SNS & Step Functions – AWS workflow automation
Java API – Experience in API development and integration
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