Data Ops - Lead Data Builder

The job profile for this position is Data Management Strategy & Governance Senior Advisor

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Job Description

• 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.

• This is a hands-on individual contributor role — the build authority that blends business fluency and data engineering discipline in equal measure, authoring Gold data products that answer the question the first time and building them to production standard.

• This role is a critical execution counterpart to Data Architecture and Data Analysis, Products & Integration, building faithfully against their designs and requirements and compressing the path from new data to a production-grade, reusable asset. It is an exciting opportunity to join the team transforming how Cigna builds and reuses data — delivered through MVP.

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

• 7+ 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.

• Gold data products are delivered and reused across use cases, with…