Description

You will bridge finance business needs with data engineering to deliver accurate, governed semantic models and reporting infrastructure for capital markets and trading systems.

This role is hybrid.

Responsibilities

• Define KPIs, business rules, and data contracts; translate them into technical specifications for warehouse and semantic layer implementation.
• Profile data, perform reconciliation, and validate data quality to ensure finance metrics are correct, auditable, and compliant.
• Design and maintain logical and dimensional data models, including star schema alignment, conformed dimensions, and hierarchies.
• Collaborate with data engineers to align ETL/ELT pipelines with modeling requirements and support schema optimization.
• Maintain comprehensive documentation, including data dictionaries, metric definitions, and semantic layer specifications.

Required Skills

• 10+ years as a Technical Business Analyst, specifically supporting Finance Data Projects.
• Deep understanding of financial data structures, KPIs, reporting needs, and reconciliation concepts.
• Expert-level SQL for extraction, transformation, validation, and performance tuning.
• Strong capability in dimensional and logical data modeling, data profiling, and data quality analysis.
• Experience with Data Warehouse architecture, ingestion/integration patterns, governance, and lineage.
• Proven experience defining and managing semantic layers for enterprise reporting and AI/ML consumers.
• Ability to translate complex business logic into structured data structures and technical specs.

Preferred Skills

• Hands-on experience with Azure SQL Database, Azure Data Factory (ADF), and Azure Databricks.
• Familiarity with orchestration tools and exposure to Power BI or Tableau semantic models.

Key Skills

Education

Not specified