Description

Key Skills: Data Engineer, Pyspark, Cloud (AWS / Azure / GCP), Python, ETL, Data Engineering, Apache Spark, PostgreSQL database

Roles and Responsibilities:

• Design, develop, and maintain robust ETL pipelines using Python and modern ETL tooling.
• Build and optimize data processing workflows with PySpark/Apache Spark for large-scale datasets.
• Write complex SQL for extraction, transformation, and loading; perform query optimization and performance tuning.
• Model and maintain relational data structures in PostgreSQL and support schema evolution.
• Implement and manage data lake/storage solutions and support distributed querying across data sources.

Skills Required:

• 6 - 9 years of relevant experience in data engineering, ETL, and pipeline development.
• ETL pipeline development and operational data workflow ownership.
• Python for data processing, automation, and integration tasks.
• PySpark/Apache Spark experience for distributed data transformations.
• Strong SQL (complex queries, optimization) and relational database experience with PostgreSQL.

Good to Have:

• Apache Iceberg and/or Delta Lake and/or Apache Hudi for data lake table management.
• Distributed SQL engines such as Trino/Presto for querying across data sources.

Education: Bachelor's degree in Computer Science, Engineering, or related field

Key Skills

Education

Any Graduate