Senior Data Engineering Consultant
Optum (UnitedHealth Group) · Healthcare & Pharma
- Gurgaon, Haryana, India
- On-site
- Posted today
- Data & AI
About the job
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.