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Job Summary
The Data Mesh / Enterprise Architect will define target-state architecture, reusable architecture patterns, and migration roadmaps for complex financial-services data environments. The role requires deep expertise in data mesh, data-product architecture, lakehouse and medallion architectures, and financial-services data, with the ability to interpret stored-procedure landscapes and establish clear ownership boundaries across domains and medallion layers. The architect will design scalable data-product patterns spanning operational applications, ingestion, market and reference data, extracts, enterprise models, master data management, sub-ledger, and risk assets. The role will work across business, data, platform, and engineering teams to establish practical architecture artifacts and ensure the platform enables domain ownership without owning underlying domain data.
Key Responsibilities
• Analyze stored-procedure landscapes from an architectural perspective and identify procedures that combine responsibilities across different domains or medallion layers.
• Define reusable target-state architecture patterns for operational applications, raw ingestion, third-party market and reference data, consumer extracts, enterprise models, MDM, sub-ledger, and risk assets.
• Map inventory items to appropriate architecture patterns and produce the pattern-assignment matrix.
• Develop the target-state conceptual architecture using DEAL, including source-aligned data products, aggregate and consumer-aligned data products, federated governance, self-service platform capabilities, and a catalogue of catalogues.
• Ensure platform provisioning capabilities are clearly separated from ownership of domain data.
• Define medallion architecture mappings for each target pattern.
• Specify output-port designs where contract-governed subscriptions replace point-to-point extracts.
• Define change-feedback mechanisms between data consumers and producers.
• Develop complexity, risk, and dependency assessments and sequence migration roadmaps accordingly.
• Produce an architecture pattern catalogue using TOGAF pattern cards.
• Develop and maintain a pattern-assignment matrix covering inventory items.
• Create target-state conceptual architecture diagrams using C4 and/or ArchiMate with supporting narrative.
• Produce complexity, risk, dependency, and sequenced roadmap documentation and diagrams.
• Collaborate with business, data, platform, and engineering teams to guide architecture decisions and implementation.
Required Qualifications
• 10+ years of experience in data architecture, including 5+ years at an enterprise or principal architecture level within financial services.
• Demonstrated hands-on delivery experience with data mesh and data-product architectures.
• Ability to describe and architect specific domain decompositions, including contested ownership boundaries and enforcement of platform-versus-domain responsibilities.
• Deep expertise in lakehouse and medallion architectures.
• Hands-on experience with Databricks, Unity Catalog, Delta, Snowflake, Kafka, Airflow, and Azure Data Lake Storage Gen2.
• Ability to evaluate and reason about equivalent AWS services and architectures, including Lake Formation, Glue Data Catalog, and Amazon DataZone.
• Strong reference and master data architecture experience, including vendor onboarding, identifier crosswalks, mastering, and distribution to consuming domains.
• Experience working with financial instrument identifiers including FIGI, LEI/GLEIF, CUSIP/ISIN, SEDOL, and MIC.
• Strong SQL Server and T-SQL expertise sufficient to analyze and decompose stored procedures based on domain and responsibility boundaries.
• TOGAF 9 or TOGAF 10 certification with demonstrable experience using TOGAF to define and govern architecture patterns.
• Production experience with ArchiMate and/or C4 modeling.
• Strong ability to develop practical architecture artifacts that can guide implementation and migration.
Preferred Qualifications
• Experience applying FIBO to taxonomy or ontology initiatives.
• Experience with ODCS or comparable data-contract specifications.
• Hands-on experience with lineage and data catalog tools such as Solidatus, Unity Catalog, Microsoft Purview, Collibra, Alation, Securiti.ai, or Anomalo.
• Experience with automated code-intelligence accelerators for SQL/SAS estate analysis.