Description

Analyse and reverse engineer complex SQL scripts and transformation pipelines to produce detailed source-to-target mappings, data lineage, and validation strategies across Medallion architecture layers.

This role is remote.

Responsibilities

• Reverse engineer multi-hop SQL and Spark SQL pipelines to document field-level lineage, joins, filters, and derivations.
• Create source-to-target mapping artifacts for Bronze, Silver, and Gold layers, including transformation rules and business logic.
• Partner with data product, architecture, and SME teams to validate assumptions, clarify definitions, and resolve data ambiguities.
• Define and implement data quality checks, reconciliation approaches, and data contracts to ensure transformation accuracy.
• Develop reusable documentation standards and support knowledge transfer to engineering teams implementing changes in Databricks.

Required Skills

• 5+ years of hands-on experience in advanced SQL, including complex joins, window functions, CTEs, and performance tuning.
• Proven experience with data mapping, source-to-target documentation, and field-level lineage for enterprise-scale platforms.
• Working knowledge of Lakehouse/Medallion architecture concepts (Bronze/Silver/Gold layering).
• Experience performing end-to-end data lineage analysis across transformations and tables.
• Ability to define and implement data quality checks and validation strategies aligned with business rules.
• Experience working with data contracts and metadata governance practices.
• Strong documentation skills with attention to detail, producing clear, audit-friendly artifacts.

Preferred Skills

• Experience in banking or financial services data domains (customer, accounts, transactions, risk, regulatory reporting).
• Familiarity with enterprise data domain and data product design initiatives.

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related discipline (or equivalent practical experience).

Key Skills

Education

Bachelor's degree