Aws Data Engineer
Job Description
We are seeking an experienced Senior AWS Data Engineer who excels in designing, building, and optimizing scalable data solutions in production cloud environments. In this role, you will leverage advanced AWS services, big data processing frameworks, and your strong ETL engineering expertise to deliver high-quality data pipelines and analytics solutions that support key business decisions.
Key Responsibilities
- Work on production-grade cloud infrastructure with key AWS services including Glue, Redshift, RDS, CloudWatch, CloudFormation, S3, IAM, and more.
- Design, develop, and optimize ETL workflows using PySpark on AWS Glue.
- Translate business and technical requirements into robust PySpark ETL code aligned with data mapping documentation.
- Build scalable data engineering solutions across big data ecosystems—covering data ingestion, automation, security, messaging, and storage.
- Develop and maintain high-performance SQL queries and data structures to improve data accessibility and accuracy.
- Ensure compliance with security standards, monitoring, and governance practices within AWS.
- Collaborate closely with cross-functional teams—data architects, analysts, and business stakeholders—to deliver data-driven solutions.
- Maintain documentation, troubleshoot production issues, and continuously optimize pipelines.
Required Skills & Experience
- 8+ years of hands-on Data Engineering experience in cloud environments.
- Strong expertise in AWS Data Services: Glue, Redshift, RDS, CloudWatch, S3, CloudFormation, IAM, etc.
- 5+ years working with large-scale Big Data ecosystems.
- 6+ years of experience in AWS Glue development.
- 4+ years of Python development experience.
- Proven ability to convert mapping documents into PySpark-based ETL processes.
- Strong proficiency in Python and SQL is mandatory.
Education Requirements
- UG: B.Tech/B.E or B.Sc – Any Specialization
- PG: Any Postgraduate (Preferred but not mandatory)