The Chief Data and Analytics Office accelerates the firm's data and analytics journey by improving data quality, integrity, and security and enabling better decision-making. The Strategy and Execution team defines and delivers the data and analytics vision and strategy, maximizing the value of data globally. This role focuses on shaping the standards, vocabularies, and models that define how data is shared responsibly at the firm — and on building the developer-friendly software that puts those models into practice at scale.
As a Vice President, Policy Engine and Data Contracts Engineer in the Chief Data and Analytics Office Strategy and Execution team, you are both a modeler and a builder. You author the firm's data-use policy model as a W3C Open Digital Rights Language (ODRL) profile, govern its evolution, and design the data contract representations that ride on top of it. In parallel, you build the Python services, application programming interfaces (APIs), and tooling that evaluate, translate, and explain those policies — across an RDF triple-store backend and large language model (LLM)-assisted authoring surfaces. You partner with legal, privacy, and engineering stakeholders to turn ambiguous policy intent into precise, machine-readable structures, and you ship working software in iterative releases.
** Job Responsibilities**
Author and maintain the firm's data-use policy model as a W3C ODRL profile, including the controlled vocabularies, constraint types, and shapes that constitute it.
Design data contract representations on top of the policy model; support authoring, validation, storage, and versioning in an RDF triple-store.
Build and maintain a Python-based ODRL policy evaluation engine that processes data-use policies against runtime requests, including permissions, prohibitions, obligations, and conflict resolution.
Develop adapters that translate policies conforming to external ODRL profiles (for example, market data services profiles) into the internal data-use policy model.
Author Shapes Constraint Language (SHACL) shapes that define what a well-formed policy looks like; implement validation, consistency checks, and regression tests for policy graphs.
Govern the evolution of the policy vocabulary as new use cases arise; align it with adjacent standards, including ODRL, Data Catalog Vocabulary (DCAT), Data Product Ontology (DPROD), and Provenance (PROV); publish model decisions and rationale.
Build English-to-ODRL and ODRL-to-English translation pipelines, including LLM-assisted drafting and explanation with guardrails.
Deliver APIs and tooling that enable stakeholders to author, review, and understand policies without reading Turtle.
Partner with legal, privacy, and engineering teams to clarify ambiguous policy text and formalize it into machine-readable form, feeding lessons back into the model.
Required qualifications, capabilities, and skills
Hands-on experience building systems with W3C ODRL, including authoring or extending profiles and evaluating real policies against runtime requests.
Demonstrated ability to design and evolve information models — controlled vocabularies, ontologies, or schemas — in collaboration with non-technical subject-matter experts.
Strong Python engineering skills, including building clean, tested, production-ready services.
Practical experience with RDF triple-stores (for example, Oxigraph, GraphDB, or Neptune), including SPARQL Protocol and RDF Query Language (SPARQL), graph management, and SHACL validation.
Working knowledge of linked-data standards, including Resource Description Framework (RDF), JavaScript Object Notation for Linked Data (JSON-LD), Turtle, RDF Schema (RDFS) / Web Ontology Language (OWL), Simple Knowledge Organization System (SKOS), and SHACL.
Familiarity with adjacent governance and metadata standards, including DCAT, DPROD, PROV, and Data Quality Vocabulary (DQV).
Ability to translate ambiguous natural language into precise logical structures, including constraints, conflict resolution, and precedence.
Willingness to engage with W3C and open-source linked-data communities to track standards evolution and feed enterprise lessons back upstream.
Ability to work in an iterative delivery cadence, including demos, feedback cycles, and incremental releases.
Preferred qualifications, capabilities, and skills
Direct contributions to W3C working groups, community groups, or open-source linked-data projects.
Experience with policy and rule engines (for example, Open Policy Agent (OPA) and Rego, or custom engines) and mapping ODRL semantics to enforcement logic.
Familiarity with LLM integration patterns (prompt engineering, structured output, and guardrails) for policy drafting and explanation.
Knowledge of data-sharing governance patterns, including purpose limitation, retention, locality, and onward-sharing constraints.
Experience with attribute-based access control and policy-based access control and how policies integrate with authorization platforms.
Experience building developer-facing tooling (command-line interfaces, APIs, or lightweight user interfaces) for ontology or policy authoring workflows.