Description

You will build and maintain scalable data pipelines and ETL/ELT workflows to support analytics needs.

This role is hybrid.

Responsibilities

• Develop and optimize data pipelines using SQL, Python, and Spark.
• Build, troubleshoot, and improve ETL/ELT workflows for efficient data ingestion and transformation.
• Perform data cleansing, validation, and quality checks on large datasets.
• Monitor pipeline performance, identify bottlenecks, and implement improvements for speed and reliability.
• Collaborate with data analysts and scientists to translate business requirements into technical solutions.

Required Skills

• 6–8 years of hands-on experience in data engineering or large-scale data processing.
• Strong proficiency in SQL and Python for data manipulation and scripting.
• Proven experience building and optimizing data pipelines using Apache Spark.
• Deep understanding of ETL/ELT development patterns and best practices.
• Ability to work with large datasets and perform rigorous data quality checks.
• Experience troubleshooting pipeline performance issues in production environments.
• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field.

Key Skills

Education

Any Graduate