Job Summary

We are looking for an experienced AWS Data Engineer with strong expertise in Python, PySpark, Databricks, and AWS to design, develop, and optimize scalable data pipelines and cloud-based data solutions. The ideal candidate should have hands-on experience with big data processing, data warehousing, and ETL development on AWS.

Key Responsibilities

- Design, develop, and maintain scalable ETL/ELT pipelines using Python and PySpark .
- Develop and optimize data processing workflows using Databricks .
- Build and manage cloud-based data solutions on AWS .
- Work with structured and unstructured data from multiple sources.
- Optimize Spark jobs for performance and cost efficiency.
- Develop reusable data engineering frameworks and automation.
- Ensure data quality, governance, security, and reliability.
- Collaborate with data analysts, data scientists, and business stakeholders.
- Troubleshoot production issues and implement performance improvements.

Required Skills





- 6+ years of experience in Data Engineering.
- Strong programming skills in Python .
- Hands-on experience with PySpark .
- Experience working with Databricks .
- Strong knowledge of AWS services such as S3, Glue, EMR, Lambda, Redshift, IAM, EC2, CloudWatch, and Athena.
- Solid SQL skills and experience with relational databases.
- Experience building scalable ETL/ELT pipelines.
- Knowledge of Delta Lake, Spark optimization, and performance tuning.
- Experience with Git and CI/CD pipelines.
- Good understanding of data modeling and data warehousing concepts.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AWS Data Engineer (Maharashtra)
🏢 Zorba AI
📍 Maharashtra