Senior Data Engineering Consultant

UnitedHealth Group; Gurugram District; On-site; INR 3,000,000 - 7,000,000; Full time

Job summary

UnitedHealth Group is seeking a senior data engineering leader to drive end-to-end data platforms, including Lakehouse, Data Warehouse, and Data Mesh architectures, while guiding cloud modernization on Azure and mentoring engineers.

You will partner with analytics teams, data scientists, and product owners to deliver scalable, secure data products and ensure governance, quality, and cost efficiency across enterprise data assets.

Qualifications

• Bachelor's Degree in a related technical discipline.
• 8+ years in Data Engineering, Data Warehousing, Data Integration, Data Modeling, and Data Platform development.
• 5+ years with Microsoft Azure and related cloud services (ADF, Databricks, ADLS Gen2, Synapse).
• 5+ years building large-scale ETL/ELT solutions (Spark, Python, SQL, Databricks, Informatica, DataStage, SSIS).
• 5+ years designing enterprise data architectures across relational, dimensional, and non-relational data platforms.
• 5+ years experience with distributed data processing (Apache Spark).
• 3+ years leading technical teams and mentoring engineers.
• 3+ years healthcare data/analytics exposure.
• Experience designing cloud-native Lakehouse and Data Warehouse architectures.
• Experience CI/CD, DevOps, IaC, and automated testing.
• Experience delivering platform modernization and migration initiatives.

Responsibilities

• Lead end-to-end data engineering lifecycle from architecture to production support.
• Drive technical strategy for data modernization and cloud transformation.
• Design scalable data platforms using Azure and modern architectures.
• Lead data acquisition and integration across diverse data sources.
• Architect and implement robust ETL/ELT pipelines for data products.
• Establish standards and reusable frameworks for scalability and maintainability.
• Provide mentorship through design reviews and code reviews.
• Lead data quality, governance, lineage, and metadata management.
• Collaborate with stakeholders to translate requirements into enterprise solutions.
• Define Lakehouse, Data Warehouse, and Data Mesh architectures for BI/AI workloads.

Skills

Data engineering

Data warehousing

Data integration

Data modeling

Distributed data processing

Team leadership

Healthcare data

Education

Bachelor's Degree in CS/IT/Engineering

Tools

Azure Data Factory

Azure Databricks

Azure Synapse

ADLS Gen2

Apache Spark

Python

SQL

Databricks

Informatica

Kafka / Event Hub

Delta Lake

Git

Azure DevOps

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:

• Lead the end-to-end data engineering lifecycle, including architecture, research, proof of concepts, design, development, testing, deployment, optimization, and production support of enterprise data solutions
• Drive technical strategy and provide leadership for complex data modernization and cloud transformation initiatives
• Design scalable, secure, and high-performing data platforms leveraging Azure cloud technologies and modern data architectures
• Lead data acquisition and integration efforts across multiple structured, semi-structured, and unstructured data sources to support enterprise analytics, reporting, AI, and operational workloads
• Architect and implement robust ETL/ELT frameworks using industry best practices for ingestion, transformation, aggregation, and delivery of data products
• Establish architecture standards, design patterns, and reusable frameworks that improve scalability, maintainability, and operational efficiency
• Provide technical leadership and mentorship to data engineers, conducting design reviews, code reviews, and enforcing engineering best practices
• Lead data quality, data governance, lineage, metadata management, and audit initiatives to ensure trusted and compliant data assets
• Partner with business stakeholders, analytics teams, data scientists, architects, and product owners to translate business requirements into enterprise data solutions
• Define and implement modern Lakehouse, Data Warehouse, and Data Mesh architectures supporting business intelligence, advanced analytics, AI/ML, and GenAI workloads
• Develop and maintain high-level architecture documents, detailed technical design specifications, and implementation roadmaps
• Drive DevOps, CI/CD, Infrastructure as Code (IaC), automated testing, and deployment automation across data platforms
• Establish proactive monitoring, observability, alerting, and reliability engineering practices to improve platform health and reduce operational incidents
• Lead performance tuning, cost optimization, troubleshooting, root-cause analysis, and production support for critical data systems
• Continuously identify opportunities for technical debt reduction, platform modernization, process automation, and operational excellence
• Promote and govern standards for documentation, security, privacy, compliance, and data management across engineering teams
• Provide solution recommendations and influence enterprise data architecture decisions across multiple programs and business domains
• Enable AI-ready data platforms and lead the implementation of GenAI, RAG, Semantic Search, Agentic AI, and intelligent data products using governed enterprise data
• Evaluate emerging technologies and recommend innovative solutions that improve business outcomes, engineering productivity, and platform capabilities
• Ensure all solutions meet enterprise requirements for scalability, reliability, security, resiliency, and cost efficiency
• Support organizational priorities and comply with all company policies, procedures, and business directives
• Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements

Required Qualifications:

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Analytics, Mathematics, or a related technical discipline
• 8+ years of experience in Data Engineering, Data Warehousing, Data Integration, Data Modeling, and Data Platform development
• 5+ years of hands‑on experience with Microsoft Azure, including Azure Data Factory, Azure Databricks, ADLS Gen2, Synapse Analytics, Event Hub, and related cloud services
• 5+ years of experience building large-scale ETL/ELT solutions using Spark, Python, Scala, SQL, Databricks, Informatica, DataStage, SSIS, or similar technologies
• 5+ years of experience designing enterprise data architectures involving relational, dimensional, and non‑relational data platforms
• 5+ years of experience managing and optimizing distributed data processing frameworks such as Apache Spark
• 3+ years of experience leading technical teams, mentoring engineers, and driving complex technology initiatives
• 3+ years of experience working with healthcare data, claims, provider, member, clinical, or healthcare analytics platforms
• Experience designing and implementing cloud‑native Lakehouse and Data Warehouse architectures
• Experience implementing CI/CD pipelines, DevOps practices, Infrastructure as Code, and automated testing frameworks
• Proven experience delivering enterprise‑scale platform modernization and migration initiatives

Preferred Qualifications:

• Master's Degree
• Azure Data Engineer Associate, Azure Solutions Architect, Databricks, or similar cloud certifications
• Hands‑on experience designing and implementing GenAI, RAG, Semantic Search, Vector Databases, and AI‑ready data platforms
• Experience integrating LLM-powered solutions with governed enterprise data assets
• Experience with healthcare data standards, compliance, security, and governance requirements
• Demonstrated ability to influence architecture decisions, drive innovation, and lead enterprise‑scale transformation initiatives

Technical Skills

• Azure Data Factory (ADF)
• Azure Databricks
• Azure Synapse Analytics
• Azure Data Lake Storage Gen2 (ADLS)
• Apache Spark
• Python
• Scala
• SQL / T-SQL / PL-SQL
• Snowflake (Preferred)
• Kafka / Event Hub
• Delta Lake / Lakehouse Architecture
• Git, Azure DevOps
• CI/CD and Infrastructure as Code
• Data Modeling and Data Governance

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.