LEAD BUSINESS ANALYST - DATA ENGINEERING

About the role

The Lead Business Analyst - Data Engineering leads the analysis and definition of business and data requirements for data pipelines, platforms, ETL/ELT workflows, and business intelligence solutions. Acting as the link between business stakeholders and technical teams, the role translates complex business needs into clear, actionable requirements that support reliable, scalable, and high-value data solutions.

Key responsibilities

• Lead the elicitation, analysis, validation, and documentation of business, data, and functional requirements for data engineering initiatives.
• Define and manage project scope, detailed work plans, source-to-target mappings (STTM), ETL/ELT data flows, and analytical use cases.
• Create data flow diagrams, data lineage maps, business scenarios, process flows, and other requirements documentation.
• Facilitate requirements interviews, design reviews, and walkthroughs with business stakeholders, data engineers, and QA/data quality teams.
• Provide technical direction, review team deliverables, and coach team members on business analysis and Agile data development practices.
• Present project status, issues, risks, assumptions, and recommendations to client stakeholders and management.
• Identify data quality, governance, reliability, and compliance risks and recommend practical solutions aligned with business objectives and audit standards.

About you

• More than 5 years of experience in business analysis within data engineering, data warehousing, or software development environments.
• Expert knowledge of business analysis tools, elicitation techniques, requirements engineering, and scope management for data projects.
• Expert-level SQL skills for data querying, analysis, reconciliation, and validation.
• Strong experience with source-to-target mapping, data lineage, data flow diagramming, ETL/ELT lifecycles, and analytical use cases.
• Strong understanding of relational and dimensional data modeling, including star schema design.
• Proven experience with Agile/Scrum, software and data engineering methodologies, and system design concepts.
• Familiarity with AWS data services such as Lambda, RDS, DynamoDB, Athena, and Kinesis, as well as modern data platform architecture.
• Demonstrated ability to lead large cross-functional meetings, data design reviews, requirements walkthroughs, and consensus-building sessions.
• Proven experience managing complex, large-scale, cross-platform data initiatives and multiple priorities.
• Strong client-facing experience, technical leadership, team leadership, and executive-level communication skills.