The Job

Data Engineer with 4+ years of experience in building scalable data pipelines, developing data assets, and delivering cloud-based data engineering solutions using modern data platforms and technologies.

Key Responsibilities

- Develop and maintain scalable data pipelines using PySpark, Databricks, and AWS.

- Optimize Spark SQL/PySpark code for performance and scalability.

- Execute data migration and modernization initiatives, including Redshift migrations.

- Refactor legacy codebases to improve maintainability and efficiency.

- Develop unit tests and support TDD practices.

- Troubleshoot complex data and performance issues.

- Manage code through Git, JFrog Artifactory, and CI/CD best practices.

Your Profile

- 4-5 years of Data Engineering experience.

- Strong hands-on experience with Databricks (AWS), PySpark,



Apache Spark, and SQL.

- Experience with AWS services such as S3, Redshift, EC2, Lambda, CloudFormation, and Athena.

- Proven experience in data migration projects and large-scale data processing.

- Strong expertise in performance tuning, code optimization, and data validation.

- Experience with source-to-target reconciliation and root cause analysis.

- Understanding of SDLC, version control, and Agile methodologies.

Positive to Have

- Power BI or reporting tools exposure.

- Knowledge of data compliance, governance, and audit requirements.

- Experience working in Agile/Scrum environments.

📌 Data Engineer (Chennai)
🏢 Edge Executive Search
📍 Chennai