Data Architect

Job Title: Data Architect with Snowflake
Location: Remote
Duration: Long Term

Required Qualifications
Financial Accounting Systems
Significant hands-on experience with one or more institutional investment accounting platforms.
Deep understanding of Accounting Book of Record (ABOR) and Investment Book of Record (IBOR) data models: differences in timing, completeness, position sourcing, and downstream use.
Experience with complex instrument representation: multi-leg derivatives, fund-of-fund look-through, private market holdings, OTC contracts.
Experience normalizing data across multiple accounting sources into a unified canonical schema — resolving structural and semantic differences between systems.
Snowflake & Cloud Data Platforms
Production experience designing and implementing layered data architectures in Snowflake:
Materialization strategy: dynamic tables, Snowpark, materialized views, virtual layers
Star schema and semantic layer design for Business Intelligence (BI) consumption (Power BI, Tableau)
Compute cost design: query optimization, clustering, partition strategy, billing-aware architecture
Snowpark for Python/Scala-based in-platform computation
Experience with medallion / layered architecture (Bronze/Silver/Gold or equivalent) with clearly defined interface contracts between layers.
Data Architecture & Modeling
10+ years of data architecture experience, with a focus on canonical and enterprise data modeling in financial services.
Proven ability to design source-agnostic data models that accommodate multiple upstream systems without requiring schema redesign.
Experience producing formal design artifacts: entity-relationship diagrams, field-level specifications, transformation rules, and Level 1/2 field classifications.
Strong grasp of data normalization principles, join key design, audit trail attributes, and lineage patterns.
Demonstrated experience maintaining and evolving data model designs across a multi-phase delivery lifecycle — managing versioning, backward compatibility, deprecation, and controlled schema evolution as product requirements grow.
Experience in asset management, wealth management, or institutional banking data domains: positions, transactions, securities, benchmarks, performance, and/or risk.