AWS Databricks Data Engineer

About the Role / Position Summary

We are hiring for a leading global digital transformation organization known for delivering large-scale enterprise data and cloud solutions to Fortune 500 clients. This role offers an opportunity to work on cutting-edge AWS and Databricks platforms, driving high-impact data engineering initiatives in a fast-paced, innovation-driven environment.

Key Responsibilities

1. Design, build, and optimize scalable data pipelines using AWS and Databricks.
2. Develop robust ETL/ELT workflows using PySpark and Python.
3. Work with large datasets to ensure high performance and data reliability.
4. Implement data processing solutions on AWS services (S3, Glue, EMR, etc.).
5. Collaborate with cross-functional teams including Data Science and Analytics.
6. Ensure data quality, governance, and security standards.
7. Troubleshoot performance issues and optimize existing pipelines.
8. Participate in architecture discussions and solution design.

Requirements / Qualifications

1. 6–12 years of experience in Data Engineering.
2. Minimum 4+ years of hands-on experience in:
3. AWS
4. Databricks
5. PySpark
6. Python
7. Strong experience in building data pipelines and distributed processing systems.
8. Good understanding of data warehousing concepts and big data frameworks.
9. Experience with performance tuning and optimization.

Preferred Skills

1. Experience with streaming frameworks (Kafka, Kinesis).
2. Exposure to Delta Lake / Lakehouse architecture.
3. Knowledge of CI/CD pipelines in data engineering.
4. Familiarity with Airflow or other orchestration tools.

Benefits

1. Competitive salary up to 28 LPA.
2. Opportunity to work on cutting-edge technologies.
3. Collaborative and innovation-driven work environment.

Application Instructions

1. Immediate joiners only.
2. Please submit your application with your resume and a cover letter.