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About the Role

We are seeking skilled Junior & Senior Data Engineers with expertise in Python, PySpark, and SQL to design, develop, and optimize scalable ETL/data transformation pipelines. The ideal candidate will have hands-on experience with large datasets, building efficient data workflows, and supporting data integration and analytics initiatives.

Responsibilities

• Design, develop, and maintain scalable ETL/data transformation pipelines using Python, PySpark, and SQL.
• Extract, transform, and load data from multiple structured and unstructured data sources.
• Develop and optimize PySpark jobs for processing large-scale datasets.
• Write efficient and complex SQL queries, stored procedures, and performance-tuned transformations.
• Perform data cleansing, validation, and quality checks to ensure data accuracy and consistency.
• Optimize data pipelines for performance, scalability, and reliability.
• Collaborate with Data Architects, Data Analysts, and Business teams to understand data requirements.
• Troubleshoot production issues and provide timely resolutions.
• Maintain technical documentation and follow coding standards and best practices.
• Participate in code reviews and continuous improvement initiatives.

Requirements

• 2–14 years of experience in Data Engineering or ETL development.
• Strong hands-on experience in Python.
• Strong expertise in PySpark for distributed data processing.
• Advanced SQL skills, including query optimization and complex joins.
• Experience in developing and maintaining ETL/data transformation pipelines.
• Good understanding of data modeling and data warehousing concepts.
• Experience handling large datasets and improving pipeline performance.
• Familiarity with Git or other version control systems.
• Strong analytical, debugging, and problem-solving skills.

Skills

• Python
• PySpark
• SQL
• Data Engineering
• ETL development
• Data modeling
• Data warehousing
• Git
• AWS
• Azure
• GCP
• Apache Spark
• Databricks
• Hadoop ecosystem
• Apache Airflow
• CI/CD pipelines
• DevOps practices

Experience Level

• Junior
• Senior
• 2-14 years