Business Data Analyst
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Key skills for this role
About the Role
HireOn Tech is seeking a Business Data Analyst with expertise in Capital Markets data modeling, Databricks, and ADLS Gen2. The role involves designing data models, creating source-to-target mappings, and optimizing Delta Lake structures.
Key Skills for This Role
Responsibilities
- Design and maintain physical and logical data models for Capital Markets domains including trade execution, portfolio positions, market data, and risk metrics
- Translate complex financial hierarchies into optimized Databricks structures
- Ensure data models support temporal requirements such as Point in Time analysis and As Of financial reporting
- Lead creation of comprehensive Source to Target Mapping documents detailing journey from legacy systems and external providers to ADLS Gen2
- Define complex 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 that prioritize shuffle free joins for massive capital markets datasets
- Implement optimized partitioning and Z Ordering strategies for time series financial data
- Utilize Unity Catalog to govern data access and maintain centralized metadata repository
Requirements
- 5+ years of experience in Capital Markets or Wealth Management with deep understanding of financial instruments and trade lifecycles
- 7+ years of experience in data modeling with mastery of Azure Databricks and ADLS Gen2
- Proven track record of creating highly detailed Source to Target Mappings for complex data migration or integration projects
- Expert level Spark SQL and PySpark
- Expertise in Delta Lake (ACID transactions, Time Travel) and Parquet optimization
- Hands on experience implementing data governance and security via Unity Catalog
Full Job Posting
Role / Skill
- Business Data Analyst for Capital Markets data modeling, Databricks, and ADLS Gen2.
JD
- 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 creation of comprehensive STM documents detailing 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 STM to guide Data Engineering squads.
- Map data lineage to ensure full traceability for regulatory compliance.
- 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.
- Utilize Unity Catalog to govern data access and maintain centralized metadata repository for 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 with 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 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.
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