Technical Business Analyst Capital Markets

Role: Business Analyst/Capital Market

Location: NYC NY / Dallas TX (Hybrid- 3 days onsite)

Only Local candidates- No relocation

Candidate Visas : No Opt No H1B

Job Description: We need a senior (10 years) Technical Business Analyst with experience supporting Finance Data Projects: Financial data structures KPIs reporting needs reconciliation concepts and data accuracy/compliance expectations. MUST HAVE EXPERIENCE WITH CAPITAL MARKETS SUPPORTING TRADING APPLICATION PROJECTS.

Primary Skills (Must-Have):

• Finance Domain Knowledge: Financial data structures KPIs reporting needs reconciliation concepts and data accuracy/compliance expectations.
• Data Modeling & Analysis: Strong capability in dimensional/logical modeling data profiling data quality analysis and translating business logic into data structures.
• Expert SQL: Advanced SQL for extraction transformation/validation performance tuning and supporting analytics/reporting use cases.

Core Technical Requirements

• Data Warehouse Expertise: Data architecture ingestion/integration patterns governance lineage and warehouse best practices.

• Semantic Layer Design (Critical): Experience defining and managing a semantic layer for enterprise reporting and AI including:

• Business definitions/metric logic conformed dimensions hierarchies
• Star schema alignment calculated measures reusable datasets
• Consistency across Power BI/Tableau and downstream AI/ML consumers

• Azure (Preferred):

• Azure SQL Database/SQL Server
• Azure Data Factory (ADF)
• Azure Databricks

• ETL/ELT & BI Tools: Familiarity with orchestration tools and exposure to Power BI and/or Tableau (semantic models/datasets).

Key Responsibilities:

• Requirements & Metric Definition: Gather/reporting & AI requirements; define KPIs business rules and data contracts; translate into technical specs for warehouse semantic layer.
• Data Analysis & Validation: Profile data identify gaps perform reconciliation and data quality checks; ensure finance metrics are correct and auditable.
• Data Modeling: Design/maintain logical and dimensional models to support reporting and AI feature readiness.
• Semantic Layer Delivery: Partner with BI/engineering to implement governed semantic models (definitions measures hierarchies security assumptions as needed).
• Collaboration with Data Engineers: Ensure pipelines/ETL align with modeling and semantic requirements; support schema optimization and efficient query patterns.
• Documentation: Maintain requirements mappings metric definitions data dictionaries and semantic layer specifications.
• Continuous Improvement: Recommend best practices/tools to improve scalability reuse and consistency across reporting and AI.

Soft Skills:

• Strong stakeholder management; able to translate business needs into technical deliverables.
• High attention to detail strong prioritization and ability to work independently in a fast-paced environment.