Data Analyst

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This role provides data analysis and data discovery support for the Focus Data Team, partnering closely with data modelers, engineers, and business stakeholders. The primary responsibility is upfront analysis of source systems, articulation of data concepts and relationships, and ownership of source-to-target mapping (Raw to Curate / Bronze to Silver) and baseline documentation that enables high‑quality, scalable data modeling and downstream data products.

This role is intentionally non-engineering focused, with accountability centered on clarity, documentation, stakeholder alignment, and readiness for development.

• Upfront Analysis
  • Conduct upfront analysis of source system data sets, structures, and business concepts, working closely with Data Modelers and Business Stakeholders to define how source data is curated into the One Focus Data Model.
  • Perform initial research and discovery, clearly articulating:
    • Core data concepts
    • Entity relationships
    • Critical attributes and their data structure
    • Assumptions, questions, and risks
    • Similarities / differences (and how we account for them) in like-source systems with differing underlying data models / architectures
  • Produce and maintain clear, structured documentation capturing findings, relationships, open questions, and concerns related to in-scope data sets
  • Partner with Data Modelers to validate, refine, and affirm data relationships and conceptual alignment prior to development
  • Support ad hoc research and analysis related to in‑scope data sets as needed after upfront discovery (e.g., data anomalies / blockers, new use cases)
  • Source to Target Mapping (STTM) + Business Documentation
    • Own the creation and maintenance of Source to Target Mapping (STTM) and supporting baseline documentation, including:
      • Standard source to target mappings
      • Transformation and derivation logic (documented, not implemented)
      • Null handling expectations and edge cases
      • Initial identification of Critical Data Elements (CDEs)
      • Entity level and attribute level descriptions aligned to the curated model
    • Act as single point of accountability for documentation quality, completeness, and on‑time delivery ahead of development

• Sprint planning or delivery estimation
• Engineering or development tasks, including:
  • Data extraction or ingestion
  • Table creation
  • Transformation logic implementation (code portion)
  • Pipeline development or orchestration

• Industry Domain
  • Generally, Wealth Management
• Concepts
  • Clients, Financial Accounts, Transactions, Billing, Financial Planning, Tax Planning – the confluence of all concepts working together
• Systems
  • CRM (Salesforce)
  • Portfolio Accounting & Billing (Industry Niche e.g., Orion, Addepar)
  • Financial Planning Tools (eMoney, Money Guide Pro)