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Big Data Engineer

Summary

Build and maintain ETL pipelines using Python, PySpark, and AWS Glue, orchestrating workflows with Step Functions and Lambda while optimizing data storage in Redshift and S3.

  • Mid Level Dev AWS Data Engineer with 4-8 years of software development experience Build and maintain ETL pipelines using Python and PySpark on AWS Glue and related platforms.
  • Orchestrate workflows using AWS Step Functions and Lambda.
  • Implement messaging and event-driven integrations using SNS and SQS.
  • Design and optimize storage and querying solutions in Amazon Redshift, RDS, Oracle and S3-based architectures.
  • Write efficient SQL for transformations, validation, and reporting.
  • Integrate data from APIs and process structured and semi-structured JSON data.
  • Implement data quality checks, monitoring, and operational support processes.
  • Participate in CI/CD and version control practices for deployment and release management.
  • Collaborate with cross-functional teams to translate business requirements into technical solutions.
  • 4-8 years of software development experience across the appropriate platform.
  • Strong hands-on experience with Python, PySpark, API’s and SQL.
  • Experience with ETL/data pipeline development and Orchestration using Step functions / AirFlow .
  • Working knowledge of AWS services including Glue, Lambda, Step Functions, Redshift, S3, SNS, and SQS.
  • Experience with Athena, EMR, Kinesis, DynamoDB, or RDS.
  • Good Knowledge on CloudWatch, logging, and production support.
  • Understanding of data warehousing, data lakes, Lake House and query optimization.
  • Experience with GitLab/Terraform or similar and CI/CD workflows.
  • Good understanding of using AI tools like Github Copilot or similar for code productivity
  • Exposure to enterprise data lake or cloud migration initiatives.
  • Have an eye to solving complex problems, great communication with stakeholders
  • Have a good understanding of performance engineering of code pipelines and near real time systems
  • Good understanding on Agents and MCP"

See also