Senior Data Engineering Consultant - Snowflake

UnitedHealth Group; Gurugram District; On-site; Confidential; Full time

Job summary

UnitedHealth Group is seeking an experienced Senior Data Engineer to design and build scalable data platforms for analytics and AI workloads in a hybrid cloud environment. You will own canonical data models, data pipelines, and governance across on-prem and cloud ecosystems.

The role requires 9+ years in software/data engineering, strong SQL and Python skills, and deep expertise with Snowflake and Databricks.

Qualifications

• Bachelor's degree in a technical field or equivalent practical experience.
• 9+ years of software/data engineering experience delivering large-scale data platforms.
• Deep experience with ETL/ELT, batch and streaming processing, and distributed data systems.
• Experience collaborating with Analytics, BI, Data Science, and Product teams to deliver reusable data assets.
• Hands-on expertise with Snowflake and Databricks.
• Cloud-based data platforms (Azure and/or GCP) including data storage, processing, orchestration, and monitoring services.
• Proven expertise in data engineering architecture, scalable pipelines, and high-availability systems.
• Advanced SQL and Python for data pipeline development.
• Solid knowledge of data quality, observability, lineage, metadata management, and governance controls.
• Ability to work across hybrid cloud/on-prem ecosystems.

Responsibilities

• Design, build, and maintain canonical data models for analytics and AI use cases.
• Define and enforce data contracts between upstream systems and downstream consumers.
• Handle schema evolution, versioning, and drift management proactively.
• Ensure alignment between business semantics and physical data models.
• Build scalable data pipelines using Snowflake, SQL, and Python; process structured and semi-structured data.
• Optimize transformations for performance, cost, and scalability; create modular components.
• Design dimensional and normalized data models for reporting, ML, and AI workloads.
• Optimize data models for BI tools and self-service analytics; support LLM consumption.
• Develop metric-layer ready models for consistent reporting.
• Implement data validation, monitoring, and quality checks; detect schema drift and data inconsistencies.
• Ensure governance, lineage, auditability, and compliance (PHI/PII, access control).
• Support enterprise data ecosystem data governance and metadata management.
• Structure data to support RAG pipelines, embeddings, and LLM-based applications.
• Enable feature-ready datasets for ML/AI use cases; collaborate with AI/ML engineers.
• Optimize Snowflake performance (clustering, partitioning, query tuning, cost management).
• Build data observability, monitoring, and alerting frameworks.
• Improve pipeline reliability, scalability, and fault tolerance.
• Design, develop, and deploy AI-powered solutions using no-code/low-code platforms.
• Comply with employment contract terms and company policies; flexible work arrangements may apply.

Skills

SQL

Python

ETL/ELT

Data pipelines

Data governance

Data observability

Data modeling

Cloud platforms

Hybrid data architectures

Big data architectures

Education

Bachelor's degree in Computer Science, Engineering, Data Engineering, or a related technical field

Tools

Snowflake

Databricks

Azure

GCP

Job description

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Primary Responsibilities:

• Data Architecture & Canonical Model Design
  • Design, build, and maintain canonical data models that serve as the single source of truth across analytics and AI use cases
  • Define and enforce data contracts between upstream systems and downstream consumers
  • Handle schema evolution, versioning, and drift management proactively
  • Ensure alignment between business semantics and physical data models
• Data Engineering & Pipeline Development
  • Build scalable and efficient data pipelines using Snowflake, SQL, and Python
  • Process both structured and semi-structured data (JSON, logs, API payloads)
  • Optimize transformations for performance, cost, and scalability
  • Implement reusable, modular pipeline components
• Advanced Data Modeling for Analytics
  • Design dimensional and normalized data models for reporting, ML, and AI workloads
  • Optimize data models for BI tools, self-service analytics, and LLM consumption
  • Develop metric-layer ready models to ensure consistency across reporting
• Data Governance & Quality
• Implement data validation, monitoring, and quality checks across pipelines
  • Build frameworks to detect schema drift and data inconsistencies
  • Ensure adherence to data governance, lineage, and auditability standards
  • Support compliance requirements (PHI/PII handling, access control, traceability)
• AI/ML & GenAI Enablement
  • Structure data to support RAG pipelines, embeddings, and LLM-based applications
  • Enable feature-ready datasets for ML and AI use cases
  • Collaborate with AI/ML engineers to ensure data readiness for agentic workflows
• Performance Optimization & Platform Engineering
  • Optimize Snowflake performance (clustering, partitioning, query tuning, cost management)
  • Build frameworks for data observability, monitoring, and alerting
  • Improve pipeline reliability, scalability, and fault tolerance
• AI Builder Responsibilities:
  • Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms, translating business needs into scalable applications that enhance products, workflows, and decision-making.
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Bachelor's degree in Computer Science, Engineering, Data Engineering, or a related technical field (or equivalent practical experience)
• 9+ years of overall experience in software engineering and data engineering roles, with significant experience designing and delivering large scale data platforms in enterprise environments
• Deep experience with ETL/ELT frameworks, batch and streaming data processing, and distributed data systems
• Experience collaborating with Analytics, BI, Data Science, and Product teams to deliver trusted, reusable, and performant data assets
• Hands‑on expertise in with Snowflakes and databricks
• Solid hands‑on experience with cloud based data platforms (Azure and/or GCP), including data storage, processing, orchestration, and monitoring services
• Proven expertise in data engineering architecture and solution design, including building, optimizing, and scaling high‑volume, high‑availability data pipelines
• Advanced proficiency in SQL and at least one programming language such as Python for data pipeline and platform development
• Solid knowledge of data quality, data observability, lineage, and metadata management, and implementing governance controls in enterprise data ecosystems
• Demonstrated ability to work across cloud and on prem ecosystems, supporting hybrid data architectures at scale

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone‑of every race, gender, sexuality, age, location and income‑deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.