Business Data Analyst

Role / Skill - Data Business Analyst

Location: Toronto, Day 1 Onsite - with 3 days at office.

JD:

• 1. Capital Markets Data Modeling
• * 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 Databricksstructures.
• • Ensure data models support temporal requirements, such as Point-in-Time (PIT) analysis and "As-Of" financial reporting.
• 2. Advanced STM (Source-to-Target Mapping) Creation
• • Lead the creation of comprehensive STM documents, detailing the journey from legacy financial systems and external providers (e.g., Bloomberg, Reuters, Aladdin) to ADLS Gen2.
• • Define complex transformation logic, business rules, and data enrichment steps within the STM to guide Data Engineering squads.
• • Map data lineage to ensure full traceability for regulatory compliance.
• 3. Databricks & ADLS Performance Engineering
• • Design Delta Lake structures that prioritize "Shuffle-free" joins for massive 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.
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Required Skills & Qualifications

• Industry Expertise: 5+ years of experience in Capital Markets or Wealth Management, with a deep understanding of financial instruments and trade lifecycles.

• Technical Modeling: 7+ years of experience in data modeling, with a mastery of Azure Databricks and ADLS Gen2.

• STM Mastery: Proven track record of creating highly detailed Source-to-Target Mappings for complex data migration or integration projects.

• Data Engine Proficiency: Expert-level Spark SQL and PySpark. Ability to optimize data structures for the 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.

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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.