Location: Toronto, Day 1 Onsite - with 3 days at office. Role / Skill: Data Business Analyst Responsibilities Design and maintain physical and logical data models for Capital Markets domains, including trade execution, portfolio positions, market data (ticks/pricing), and risk metrics. Translate complex financial hierarchies (e.g., fund-of-funds, multi-asset class structures) into optimized Databricks structures. Ensure data models support temporal requirements, such as Point‑in‑Time (PIT) analysis and “As‑Of” financial reporting. Lead the creation of comprehensive Source‑to‑Target Mapping (STM) documents detailing the journey from legacy financial systems and external providers (Bloomberg, Reuters, Aladdin) to ADLS Gen2. Define transformation logic, business rules, and data enrichment steps within STM to guide Data Engineering squads. Map data lineage to ensure full traceability for regulatory compliance. Design Delta Lake structures prioritizing “Shuffle‑free” joins for large capital markets datasets. Implement optimized partitioning and Z‑Ordering strategies specifically for time‑series financial data to enable high‑speed analytics. Utilize Unity Catalog to govern data access and maintain a centralized metadata repository for the GWAM ecosystem. Required Skills & Qualifications Industry Expertise: 5+ years in Capital Markets or Wealth Management, with deep understanding of financial instruments and trade lifecycles. Technical Modeling: 7+ years in data modeling, mastery of Azure Databricks and ADLS Gen2. STM Mastery: Proven track record of creating detailed Source‑to‑Target mappings for complex data migration or integration projects. Data Engine Proficiency: Expert‑level Spark SQL and PySpark, with ability to optimize data structures for Spark Catalyst Optimizer. Storage Formats: Expertise in Delta Lake (ACID transactions, Time Travel) and Parquet optimization. Governance: Hands‑on experience implementing data governance and security via Unity Catalog. Technical Stack Compute: Azure Databricks (Jobs, SQL Warehouses) Storage: ADLS Gen2 (Delta/Parquet) Governance: Unity Catalog Analysis Tools: SQL, Python, Excel (for data profiling) Documentation: Confluence/Visio for STM and ERDs #J-18808-Ljbffr