Data Warehouse Engineer

Job Responsibilities

• Design, build, and maintain ETL/ELT pipelines to support efficient data integration and transformation (Python, PySpark, SQL)
• Develop and manage data models and database components (e.g., stored procedures) to orchestrate and optimize data workflows
• Drive and enhance DevOps best practices, including CI/CD pipelines and automation
• Continuously improve data platform capabilities by evaluating and leveraging emerging technologies, tools, and methodologies
• Identify opportunities to incorporate AI and advanced analytics to improve data processes, platform capabilities, and the solutions delivered to business users
• Partner with data scientists and analysts to deliver impactful, data-driven solutions
• Collaborate with upstream and downstream system owners to ensure smooth and reliable integration
• Monitor data pipelines and Azure cloud infrastructure to ensure stable day-to-day operations
• Track, analyze, and improve platform performance metrics to identify bottlenecks and data pipeline issues
• Resolve service requests as part of 2nd and 3rd level support
• Mentor and support team members, trainees, and students

Qualifications

• A bachelor's degree in Computer Science, Data Science/Engineering or related field is required
• 5+ years of experience in data engineering, software engineering, or similar roles is required
• Some minimal international travel is required
• Demonstrated ability to work independently as well as within a team
• Strong proficiency in SQL development
• Experience with Python and/or PySpark
• Solid understanding of data pipelines, ETL/ELT processes, and data modeling
• Experience with Azure Synapse Analytics, Azure Data Factory, Microsoft Fabric, Azure Data Lake Storage Gen2 / OneLake, Azure SQL Server, and Azure DevOps, including Git and CI/CD pipelines (YAML)
• Strong analytical, troubleshooting, and problem-solving skills
• Structured, reliable, and collaborative working style