Data Governance / Target Operating Model (TOM) Lead, New York, NY (Hybrid- 3 Days Onsite)

Data Governance / Target Operating Model (TOM) Lead Location: New York, NY (hybrid 3 days from office)

W2 Position! 

Immediate Position! We have a good hold on this position!

Our challenge

Client is seeking an experienced Data Governance & Operating Model Lead to design and implement a federated data-governance model across a banking or capital-markets environment. The role will establish a canonical business taxonomy, define clear domain boundaries, assign accountable producing domains and develop producer-consumer data contracts. Candidate will translate complex dependency and lineage findings into practical ownership, stewardship and contract obligations, while ensuring that the target governance model is embedded into the organisation’s architecture and operating practices. The successful candidate will be comfortable working at enterprise scale, challenging ambiguous ownership decisions and producing governance artefacts that are practical for domain teams and defensible to internal audit, regulators and senior stakeholders.

Responsibilities:

•  Agree the taxonomy normalisation method and the metadata standard (ISO/IEC 11179)
• Establish the four boundary tests as the documented decision method: business capability rather than schema; origination beats usage; change cadence and cohesion; accountability for the business decision the data supports.
• Normalise the inventory into a canonical, FIBO-informed taxonomy with explicit boundary definitions, collapsing variants such as "Reference" / "Market Data" / "Reference / Market Data", "Equities Front Office" versus "Equity Front Office", and the several spellings of "Derivatives Operations (Reg Ops)".
• Assign exactly one accountable producing domain to every item and produce the domain-assignment matrix with written rationale (DDD context mapping).
• Resolve multi-domain and contested items through DACI. Contested artefacts, typically cross-domain stored procedures — are decomposed into origination logic held by the producer and derivation logic held as a consumer-side product; they are not shared.
• Convert the dependency and lineage map into named consuming domains and contract obligations for every UI, extract feed and downstream application.
• Draft provisional producer-consumer data contracts to ODCS, each specifying all six mandatory elements: schema and semantics; quality SLOs; freshness and availability; access and entitlement; versioning; change and deprecation.
• Define the target operating model across the four roles: Domain Owner (accountable), Data Product Owner (responsible), Data Steward (quality and metadata), Platform team (enablement, never ownership) — with a stewardship RACI that names real people or real positions
• Supply the governance plane definition into the target-state architecture: taxonomy conformance, contract registry, policy-as-code, quality SLOs and access entitlement enforced at the point of publish.
• Advise on adoption sequencing, which domains are ready to hold accountability on day one and which need an interim arrangement. 

Requirements:

• 10+ years in data governance within banking or capital markets; 5+ leading governance or TOM design at enterprise scale.
• Federated governance design experience, evidence of a model that was adopted by domain teams, not a policy set that was published and ignored. Ask for the adoption evidence.
• Domain-Driven Design context mapping applied to data domains, and working familiarity with FIBO and BIAN service domains as sources of canonical boundaries.
• Data contract standards (ODCS or equivalent) and metadata registry standards (ISO/IEC 11179).
• Regulatory grounding that makes the governance defensible under examination: BCBS 239 principles, critical data element definition and coverage, Dodd-Frank, MiFID II
• Practical facility with catalogue, lineage and data-quality tooling: Unity Catalog, Microsoft Purview, Collibra, Alation, Solidatus, Securiti.ai, Anomalo.
• Ability to write a decision rationale that will still be defensible to an internal auditor two years from now.

Preferred, but not required:

• Domain-assignment matrix with rationale (Excel; DDD context mapping)
• Refined domain taxonomy and boundary definitions (Word; DDD + FIBO)
• Target operating model for ownership and stewardship (Word + RACI)
• Provisional producer-consumer data contracts (YAML/Excel; ODCS)