Data Management Strategy & Governance Advisor

This Data Management Strategy & Governance Advisor role offers an exciting opportunity to build on your strengths, expand your impact, and continue growing within the organization.

The Data Builder is the hands-on builder responsible for turning architectural design and business requirements into trusted, reusable data products through MVP that are production grade. Reporting to the Senior Director, Data Operations & Data Management, this role builds to the enterprise-agnostic Silver foundation designed by Data Architecture and co-designs and builds Gold data products where business logic, metrics, and functional knowledge live.

Key Responsibilities

Rapid Build & Delivery

• Build architecture's designs and analysis's requirements into production-ready solutions through MVP.
• Work new and unfamiliar data quickly into a working solution that answers the business question at hand.
• Refactor learning-stage and bespoke work into durable, reusable, production-ready assets.

Silver , Build to Architecture's Design

• Build the physical Silver structures to the enterprise-agnostic Silver model and reference patterns designed by Data Architecture.
• Implement the design faithfully and promote it to production through governed CI/CD pipelines.
• Capture business context and metadata at build, and hand off to trusted partner teams as readiness allows.

Gold , Democratized, Delivered Through MVP

• Treat the Gold layer as democratized , Data Operations may own specific Gold assets and assists other teams in building theirs.
• Deliver Gold solutions through build-through-MVP, promoted to production-grade through governed CI/CD pipelines regardless of owner.
• Uphold the build standards and guardrails any Gold solution must meet, so a federated Gold layer stays stable and production-grade across owning teams.

Engineering Discipline & Production Readiness

• Build to production standards from day one so the lift from MVP to production is simple, not a rebuild.
• Apply consistent development patterns, naming conventions, and build standards with specific focus on the connectivity across all data products to create a more connected data ecosystem.
• Move work through the CI/CD pipeline , develop, test, and productionize , clearing quality, security, and cost checks on first pass.
• Apply AI and automation to accelerate build and testing without bypassing governance, security, or quality expectations.

Partnership & Collaboration

• Partner with Data Architecture , building to their Silver design and co-designing Gold within the standards they set.
• Partner with Data Analysis, Products & Integration , who bring the requirements, business rules, and acceptance criteria this role builds against.
• Partner with Platform Engineering / IT and DevOps & AI Enablement , who own ingestion, pipelines, and the automation frameworks this role builds on.
• Partner with data science and business analytics teams so Gold data products serve their models, analyses, and decisions.
• Set the design and hold Data Operations standards across the Hyderabad Data Operations team and outside service partners as part of a global delivery model.

What This Role Is Not

• Not a pure data engineering or platform role.
• Not the owner of the enterprise Silver model.
• Not the primary business-engagement or requirements role.
• Not the owner of the Gold layer, which is democratized across teams.
• Not a governance policy, stewardship, or BI reporting role.
• This role exists to build real data solutions that get used , designed for the business, engineered to last, delivered through MVP.

Required Experience & Capabilities

• 3+ years building production-grade data solutions, with demonstrated depth in analytics engineering or equivalent business-plus-build work.
• A genuine 50/50 blend of business fluency and hands-on engineering discipline.
• Hands-on experience with Databricks, Spark, Unity Catalog, SQL, and Python.
• Familiarity with Snowflake and Teradata in addition to a Databricks-first stack.
• Expert knowledge of dimensional and medallion (Silver / Gold) modeling within an enterprise-agnostic data model.
• Working knowledge of CI/CD pipelines, automated code evaluation, and controlled promotion to production.
• Strong software-engineering discipline , version control (Git), code review, and efficient, reusable code.
• Performance-tuning and cost-optimizing Spark and SQL transformations at scale.
• Familiarity with data governance and cataloging tooling such as Collibra.
• Automated data-quality testing and validation built into every solution.
• Demonstrated ability to learn a new data domain fast and turn business logic into reusable data products.
• Demonstrated ability to apply AI and automation to accelerate build while preserving quality and governance.
• Experience in complex, regulated enterprises preferred; healthcare or PBM data a plus.

Measures of Success

• New data reaches a trusted, production-grade asset in a short cycle time.