Description

Lead the design, development, and maintenance of enterprise ETL pipelines and data solutions. Own the translation of business requirements into technical data warehouse architectures. Drive continuous optimization of data processes and ensure high-quality delivery of data engineering projects.

Responsibilities

• Design and build robust ETL pipelines using Python, PySpark, and SQL within AWS or Azure environments.
• Translate business requirements and data mapping documents into detailed technical designs and data warehouse schemas.
• Develop unit tests and support system integration and regression testing to ensure data integrity.
• Troubleshoot and resolve complex issues across development, testing, and production environments.
• Mentor junior developers, lead specific projects, and collaborate with cross-functional teams to manage risks and blockers.

Required Skills

• 5+ years of experience in ETL development within enterprise data warehouse environments.
• Strong proficiency in Python, PySpark, and SQL for data processing and transformation.
• Hands-on experience with IBM DataStage or similar enterprise ETL tools.
• 3+ years of experience working with cloud platforms, specifically AWS or Azure, including migration projects.
• Solid understanding of data warehousing concepts, architecture, and industry best practices.
• Bachelor’s degree in Computer Science or a related field.
• Proven ability to lead projects and provide technical guidance to team members.

Preferred Skills

• Experience with modern cloud data platforms such as Snowflake.
• AWS certifications (Solutions Architect, DevOps Engineer, or Professional level).

Key Skills

Education

Bachelor's degree