Data Ops - Lead Data Builder

The Cigna Group•Remote,

21h•$115,200 - $192,000

About The Position

The Data Builder is a hands-on individual contributor who turns architectural designs and business requirements into trusted, reusable data products, delivering through MVP and building to production standards. The role builds physical Silver structures to the enterprise-agnostic model and reference patterns designed by Data Architecture, and co-designs and builds Gold data products where business logic, metrics, and functional knowledge reside. The role is an execution partner to Data Architecture and Data Analysis, Products & Integration, building against their designs and requirements and shortening the path from new data to production-grade reusable assets. It applies business fluency and data engineering discipline to create solutions that answer business questions and are stable, governed, and production-ready. The position partners with platform engineering, IT, DevOps and AI Enablement, data science, business analytics, and external service partners. It sets and upholds build standards across the Hyderabad Data Operations team and outside service partners as part of a global delivery model. It does not own the enterprise Silver model or the democratized Gold layer, nor is it primarily a requirements, governance policy, stewardship, or BI reporting role.

Requirements

At least 7 years building production-grade data solutions, with demonstrated depth in analytics engineering or equivalent business-plus-build work.
A genuine balance of business fluency and hands-on engineering discipline.
Hands-on experience with Databricks, Spark, Unity Catalog, SQL, and Python.
Familiarity with Snowflake and Teradata, alongside 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, including version control (Git), code review, and efficient, reusable code.
Ability to performance-tune and cost-optimize Spark and SQL transformations at scale.
Familiarity with data governance and cataloging tools such as Collibra.
Ability to build automated data-quality testing and validation into every solution.
Demonstrated ability to learn a new data domain quickly and turn business logic into reusable data products.
Demonstrated ability to apply AI and automation to accelerate building while preserving quality and governance.

Nice To Haves

Experience in complex, regulated enterprises.
Healthcare or PBM data experience.

Responsibilities

Build architectural designs and analysis requirements into production-ready solutions through MVP.
Work new and unfamiliar data quickly into a working solution that answers the business question.
Refactor learning-stage and bespoke work into durable, reusable, production-ready assets.
Build physical Silver structures to the enterprise-agnostic Silver model and reference patterns designed by Data Architecture.
Implement Silver designs faithfully and promote them to production through governed CI/CD pipelines.
Capture business context and metadata during build and hand off to trusted partner teams as readiness allows.
Deliver Gold solutions through build-through-MVP and promote them to production grade through governed CI/CD pipelines, regardless of ownership.
Uphold build standards and guardrails for Gold solutions so the federated Gold layer remains stable and production grade across teams.
Build to production standards from day one, using consistent development patterns, naming conventions, and build standards, with focus on connectivity across data products.
Move work through CI/CD pipelines by developing, testing, and productionizing solutions, clearing quality, security, and cost checks on first pass.
Apply AI and automation to accelerate building and testing without bypassing governance, security, or quality expectations.
Partner with Data Architecture on Silver designs and co-design Gold within established standards.
Partner with Data Analysis, Products & Integration to build against requirements, business rules, and acceptance criteria.
Partner with Platform Engineering / IT and DevOps & AI Enablement, building on their ingestion, pipeline, and automation frameworks.
Partner with data science and business analytics teams to ensure Gold data products serve their models, analyses, and decisions.
Set design and hold Data Operations standards across the Hyderabad Data Operations team and outside service partners.
Deliver trusted, production-grade assets with short cycle times, reusable Gold products, faithful Silver implementations, and governed production releases.