Senior Data Engineering Consultant

Data Engineer

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 & Design
  • Design, build, and maintain scalable data pipelines, ETL/ELT workflows, and data integration solutions
  • Define and enforce data modeling standards, including dimensional, relational, and NoSQL models
  • Architect and optimize data lakes, data warehouses, and lake house platforms (e.g., Azure Synapse, Databricks, Snowflake, Big Query, Redshift)
  • Ensure solutions are aligned with enterprise architecture, scalability needs, and performance expectations
• Technical Leadership
  • Lead a team of data engineers, providing technical mentorship, code reviews, and best practice guidance
  • Drive the adoption of modern data engineering frameworks (Spark, Kafka, Delta Lake, Airflow, etc.)
  • Establish engineering standards for coding, testing, CI/CD, version control, and documentation
  • Evaluate and recommend new tools, technologies, and platforms
• Data Pipeline Development & Optimization
  • Build and optimize real time, batch, and streaming data pipelines
  • Implement data ingestion from multiple sources: APIs, databases, message queues, cloud storage
  • Monitor and optimize pipeline performance, cost, reliability, and throughput
  • Implement automation to reduce manual operations and improve pipeline resiliency
• Data Quality & Governance
  • Define and implement data quality frameworks (validation, lineage, reconciliation)
  • Ensure data security, privacy, and compliance with standards (HIPAA, GDPR, SOC2, etc.)
  • Maintain metadata, lineage, and cataloging using tools like Purview, Collibra, Alation, etc.
• Collaboration & Stakeholder Engagement
  • Work closely with data scientists, analysts, product owners, and business leaders to understand requirements
  • Translate business needs into scalable technical designs and data solutions
  • Partner with cloud engineering, DevOps, and architecture teams to ensure smooth production operations
• Cloud & DevOps Enablement
  • Lead cloud‑based data engineering implementations (Azure, AWS, GCP)
  • Implement and maintain CI/CD pipelines, Infrastructure‑as‑Code (IaC), monitoring, and alerting
  • Optimize cloud resources for cost‑efficient and high‑performance data processing
• Production Support & Operations
  • Oversee the reliability and uptime of production data pipelines
  • Respond to production incidents, perform root cause analysis, and drive long‑term fixes
  • Establish SLA/SLO metrics, monitoring dashboards, and operational runbooks
• Strategic Planning
  • Contribute to data roadmap, platform modernization, and long term architecture strategy
  • Identify opportunities to improve data availability, accessibility, and analytics enablement
  • Ensure alignment with organizational goals and future technology trends
• 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 regard 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:

• Undergraduate degree or equivalent experience.
• Data Engineering & ETL
  • Hands‑on experience with streaming technologies (Kafka, EventHub, Kinesis, Flink, Structured Streaming)
  • Solid proficiency in building ETL/ELT pipelines using Spark, PySpark, SQL, Scala, or Python
• Cloud Platforms
  • Experience with at least one enterprise cloud:
    • Azure: Databricks, Synapse, Data Factory, ADLS, Purview
    • AWS: Redshift, Glue, EMR, S3, Lambda
    • GCP: BigQuery, Dataflow, Dataproc, Cloud Storage
• Data Storage & Modeling
  • Expertise in data lake, data warehouse, and lakehouse architectures
  • Solid understanding of dimensional modeling, relational design, NoSQL stores (CosmosDB, DynamoDB, MongoDB)
• DevOps & Automation
  • Experience with CI/CD pipelines, Git, Azure DevOps, Github Actions, Terraform, or other IaC tools
  • Familiar with containerization (Docker, Kubernetes) and cluster‑based processing
• Data Quality & Governance
  • Knowledge of data quality tools, metadata management, lineage frameworks
  • Understanding of regulatory compliance (HIPAA, GDPR, SOC2).

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.