Data Engineer
About The Position
Key Responsibilities· Design, develop, and maintain ETL pipelines using AWS Glue, Glue Studio, and Glue Catalog.· Ingest, transform, and load large datasets from structured and unstructured sources into AWS data lakes/warehouses.· Work with S3, Redshift, Athena, Lambda, and Step Functions for data storage, query, and orchestration.· Build and optimize PySpark/Scala scripts within AWS Glue for complex transformations.· Implement data quality checks, lineage, and monitoring across pipelines.· Collaborate with business analysts, data scientists, and product teams to deliver reliable data solutions.· Ensure compliance with data security, governance, and regulatory requirements (BFSI preferred).· Troubleshoot production issues and optimize pipeline performance. Required Qualifications· 9+ years of experience in Data Engineering, with at least 5+ years on AWS cloud data services.· Strong expertise in AWS Glue, S3, Redshift, Athena, Lambda, Step Functions, CloudWatch.· Proficiency in PySpark, Python, SQL for ETL and data transformations.· Experience in data modeling (star, snowflake, dimensional models) and performance tuning.· Hands-on experience with data lake/data warehouse architecture and implementation.· Strong problem-solving skills and ability to work in Agile/Scrum environments. Preferred Qualifications· AWS Certified Data Analytics – Specialty or AWS Solutions Architect certification.· Familiarity with CI/CD pipelines for data engineering (CodePipeline, Jenkins, GitHub Actions).· Knowledge of BI/Visualization tools like Tableau, Power BI, QuickSight.
Requirements
- 9+ years of experience in Data Engineering, with at least 5+ years on AWS cloud data services.
- Strong expertise in AWS Glue, S3, Redshift, Athena, Lambda, Step Functions, CloudWatch.
- Proficiency in PySpark, Python, SQL for ETL and data transformations.
- Experience in data modeling (star, snowflake, dimensional models) and performance tuning.
- Hands-on experience with data lake/data warehouse architecture and implementation.
- Strong problem-solving skills and ability to work in Agile/Scrum environments.
Nice To Haves
- AWS Certified Data Analytics – Specialty or AWS Solutions Architect certification.
- Familiarity with CI/CD pipelines for data engineering (CodePipeline, Jenkins, GitHub Actions).
- Knowledge of BI/Visualization tools like Tableau, Power BI, QuickSight.
Responsibilities
- Design, develop, and maintain ETL pipelines using AWS Glue, Glue Studio, and Glue Catalog.
- Ingest, transform, and load large datasets from structured and unstructured sources into AWS data lakes/warehouses.
- Work with S3, Redshift, Athena, Lambda, and Step Functions for data storage, query, and orchestration.
- Build and optimize PySpark/Scala scripts within AWS Glue for complex transformations.
- Implement data quality checks, lineage, and monitoring across pipelines.
- Collaborate with business analysts, data scientists, and product teams to deliver reliable data solutions.
- Ensure compliance with data security, governance, and regulatory requirements (BFSI preferred).
- Troubleshoot production issues and optimize pipeline performance.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
11-50 employees
