Data Ops - Data Builder

The Cigna Group•Remote,

21h•$102,400 - $170,600

About The Position

The Data Builder is a hands-on individual contributor who turns architectural designs and business requirements into trusted, reusable data products through MVP and brings them to production-grade quality. The role builds the enterprise-agnostic Silver foundation designed by Data Architecture and co-designs and builds Gold data products that contain business logic, metrics, and functional knowledge. It combines business fluency with data engineering discipline and serves as an execution partner to Data Architecture and Data Analysis, Products & Integration. The role builds physical Silver structures to established models and reference patterns, and develops Gold products within shared standards and guardrails. It promotes solutions through governed CI/CD pipelines, captures business context and metadata, and collaborates with partner teams on handoff and readiness. The position applies production engineering standards, testing, security and cost checks, and AI and automation while maintaining governance and quality expectations. The role reports to the Senior Director, Data Operations & Data Management. It is part of a global delivery model and helps set and maintain Data Operations standards across the Hyderabad team and external service partners. The position is not the owner of the enterprise Silver model or the democratized Gold layer, and is not primarily a platform, requirements, governance, stewardship, or BI reporting role.

Requirements

At least 3 years of experience building production-grade data solutions, with demonstrated depth in analytics engineering or equivalent business-plus-build work.
A balanced combination 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, 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.
Experience building automated data-quality testing and validation into solutions.
Ability to learn a new data domain quickly and turn business logic into reusable data products.
Ability to apply AI and automation to accelerate development while preserving quality and governance.

Nice To Haves

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

Responsibilities

Build architectural designs and business requirements into production-ready solutions through MVP.
Work with new and unfamiliar data quickly to create solutions that answer business questions.
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 development and hand off to trusted partner teams as readiness allows.
Build Gold data products through MVP, whether owned by Data Operations or other teams, and promote them to production-grade through governed CI/CD pipelines.
Uphold build standards and guardrails so the federated Gold layer remains stable and production-grade.
Apply consistent development patterns, naming conventions, and build standards, with attention to connectivity across data products.
Develop, test, and productionize work through CI/CD pipelines, meeting quality, security, and cost checks.
Use AI and automation to accelerate building and testing without bypassing governance, security, or quality expectations.
Partner with Data Architecture on Silver design and Gold co-design 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 to build on their ingestion, pipelines, and automation frameworks.
Partner with data science and business analytics teams so Gold data products support their models, analyses, and decisions.
Set and maintain Data Operations standards across the Hyderabad team and external service partners as part of a global delivery model.