Enterprise Solutions Architect
About the role
We are seeking an experienced Data Mesh / Enterprise Architect to define the target-state architecture for a complex financial-services data estate. You will translate detailed stored procedures and data-landscape analysis into an actionable enterprise architecture. This includes defining domain and medallion-layer boundaries, creating reusable architecture patterns, designing source-aligned and consumer-aligned data products, and establishing the governance and platform capabilities required to support a federated data mesh. The role requires genuine delivery experience in data-product architecture—not simply familiarity with data mesh concepts. You will need to make practical architectural decisions across legacy SQL estates, lakehouse platforms, reference and master data, data contracts, lineage and enterprise architecture governance. Work Location: New York City, NY (Hybrid, 3 days in a Week).
Responsibilities
- Interpret the stored-procedure landscape analysis architecturally: where a single procedure conflates responsibilities belonging to different domains or different medallion layers, define how it is split.
- Define one reusable target pattern per MCDB feature class: operational UI / applications (app), raw ingestion from systems of record (stage), third-party market and reference data (refdata), consumer extracts (extract), enterprise model, and the cross-cutting MDM, sub-ledger and risk assets.
- Map every inventory item to a pattern and produce the pattern-assignment matrix.
- Compose the target-state conceptual architecture on DEAL: source-aligned data products, aggregate and consumer-aligned data products, the federated governance plane, the self-serve platform and the catalogue of catalogues with the platform provisioning capability but never owning domain data.
- Define the medallion mapping for each pattern.
- Specify output-port design so that contract-governed subscriptions replace point-to-point extracts, and define the change-feedback loop from consumer to producer.
- Produce the complexity, risk and dependency assessment and sequence the roadmap against it.
- Deliverables owned: Architecture pattern catalogue, one per feature class (Word; TOGAF pattern cards)
- Pattern-assignment matrix covering every inventory item (Excel)
- Target-state conceptual architecture (C4 and/or ArchiMate diagram + narrative)
- Complexity, risk and dependency assessment with sequenced roadmap (Word + diagram)
Requirements
- 10+ years in data architecture, 5+ at enterprise or principal level in financial services.
- Genuine data mesh / data-product architecture delivery, not familiarity with the literature. Candidates must be able to describe a specific domain decomposition they authored, the contested boundaries within it, and how the platform-versus-domain responsibility split was enforced.
- Deep lakehouse and medallion architecture: Databricks with Unity Catalog, Delta, Snowflake, Kafka, Airflow, Azure Data Lake Storage Gen2. Must be able to reason about equivalents on AWS (Lake Formation, Glue Data Catalog, Amazon DataZone).
- Reference and master data architecture: vendor onboarding, identifier crosswalks across FIGI, LEI/GLEIF, CUSIP/ISIN, SEDOL and MIC, mastering and distribution to consuming domains.
- SQL Server and T-SQL depth sufficient to reason about stored-procedure decomposition the ownership boundaries in MCDB are inside the procedures, not the schema names.
- TOGAF 9 or 10 certified, with demonstrable use of TOGAF to define and govern patterns; ArchiMate or C4 modelling in production use.