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 up-to-date 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. Good to Have
- Power BI or reporting tools exposure.
- Knowledge of data compliance, governance, and audit requirements.
- Experience working in Agile/Scrum environments.

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