Purpose of the Job

The Lead Data Engineer is a senior individual contributor role within the Data & Analytics organization. This position does not carry people management or direct reporting responsibilities but plays a critical hands‑on role in delivering high‑quality, reliable, and scalable data solutions.

The role requires strong technical depth, quick problem‑solving ability, and ownership of data engineering tasks and initiatives. The Lead Data Engineer is expected to work independently, collaborate closely with cross‑functional teams, and drive data issues and projects to closure with speed and accuracy.

Data Engineering & Delivery

• Design, develop, and maintain robust data pipelines for ingesting, transforming, and delivering structured and semi‑structured data.
• Build and optimize SQL‑based data models to support BI, reporting, and analytical use cases.
• Write efficient, scalable, and well‑tested SQL and Python code.
• Ensure data accuracy, completeness, and consistency through validation and quality checks.

Troubleshooting & Support

• Quickly analyze data issues, identify root causes, and implement effective fixes.
• Support production data pipelines and analytical datasets to ensure stability and reliability.
• Proactively monitor data processes and address performance or quality concerns.

Collaboration & Ownership

• Work closely with BI analysts, data scientists, product teams, and business stakeholders to understand requirements and deliver solutions.
• Take end‑to‑end ownership of assigned tasks, enhancements, and data issues until closure.
• Participate in design discussions and provide practical, solution‑oriented recommendations.

Continuous Improvement

• Contribute to improving data engineering standards, best practices, and documentation.
• Support knowledge sharing and technical discussions within the data team.
• Stay current with modern data engineering tools, frameworks, and techniques

Job Requirements - Experience and Education

• Bachelor’s degree in computer science, Engineering, or a related field.
• Typically, 5–8 years of hands‑on experience in data engineering, BI engineering, or a similar data‑focused role.

Technical Requirements

• Very strong proficiency in SQL, including complex queries, performance tuning, and data modelling.
• Strong hands‑on experience with Python for data processing, automation, and problem‑solving.
• Solid understanding of ETL / ELT concepts and data pipeline design.
• Experience working with relational databases and modern data platforms (cloud data warehouses, data lakes, or similar).
• Exposure to at least one cloud platform such as Azure, AWS, or GCP, including working with cloud‑based data storage, compute, or analytics services.
• Familiarity with batch data processing and basic streaming concepts.
• Experience using version control and collaboration tools (e.g., Git, JIRA, Confluence).
• Prior experience in a data or technology support role (production support, BI support, data ops, etc.) is a plus, with the ability to troubleshoot and resolve issues under time pressure.

Leadership Behaviors

Skills