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Data Engineering Lead - Python, Pyspark, Azure Databricks

Pay
Pay not listed
Work setting
Not stated
Employment
Not stated

What you’ll work on

Full posting
  • Design and maintain batch and streaming pipelines on Azure Databricks and Delta Lake

  • Write PySpark and Spark SQL transformations for CDC, SCD Type 1/2 and deduplication

  • Implement Unity Catalog governance, row/column security and PHI/PII protection

  • Tune Spark jobs and Delta tables for performance and cost

  • Troubleshoot production issues and mentor junior engineers

From the employer’s posting
Design, build and maintain scalable batch and streaming data pipelines on Azure and Databricks
Develop complex transformations in PySpark and Spark SQL, including CDC, SCD Type 1/2, deduplication
Implement data governance, lineage and security using Unity Catalog, including row/column-level security and PHI/PII protection
Tune Spark jobs and Delta tables for performance and cost
Troubleshoot production issues, do root cause analysis and put preventive fixes in place

What you’ll bring

All qualifications

Core experience

  • 6+ years of data engineering experience, including 3+ years hands-on with Azure Databricks
  • Hands-on experience with Delta Lake, Lakehouse architecture and Unity Catalog
  • Experience working with file formats such as CSV, JSON, XML, Parquet, Avro and Delta, including schema inference, schema evolution and nested data handling
  • Experience with Azure services: ADF, ADLS Gen2, Key Vault, Azure SQL , Power Bi
  • Solid knowledge of data modeling, ETL/ELT design, Git, CI/CD and Agile delivery
  • Good understanding of views, temporary/global temporary views, materialized views, streaming tables and when to use each

Preferred experience

  • Experience with Structured Streaming, Kafka/Event Hubs, Lakeflow Jobs and Databricks SQL
  • Experience with Power BI or AI/BI dashboards
  • Experience mentoring or leading a team, or driving cloud migration and modernization
Qualification wording
6+ years of data engineering experience, including 3+ years hands-on with Azure Databricks
Hands-on experience with Delta Lake, Lakehouse architecture and Unity Catalog
Experience working with file formats such as CSV, JSON, XML, Parquet, Avro and Delta, including schema inference, schema evolution and nested data handling
Experience with Azure services: ADF, ADLS Gen2, Key Vault, Azure SQL , Power Bi
Solid knowledge of data modeling, ETL/ELT design, Git, CI/CD and Agile delivery
Good understanding of views, temporary/global temporary views, materialized views, streaming tables and when to use each
Experience with Structured Streaming, Kafka/Event Hubs, Lakeflow Jobs and Databricks SQL
Experience with Power BI or AI/BI dashboards
Experience mentoring or leading a team, or driving cloud migration and modernization
Apply at UnitedHealth Group

Posting record

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Actively hiringFirst seen by us 8 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 27, 20268 days ago
Recorded sightings
24
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 8

Similar jobs usually come down between day 5 and day 54.

From 10,704 similar postings that came down. Coming down is not always a hire.

UnitedHealth Group is hiring

159 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring is steady
  • Takes jobs down quickly
  • 11% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • Azure
  • Databricks
  • Delta Lake
  • Excel
  • Kafka
  • Power BI
  • Spark
  • PySpark
Where the posting names them
- Good understanding of views, temporary/global temporary views, materialized views, streaming tables and when to use each - Solid proficiency in Python, PySpark and SQL, with a solid understanding of Spark internals and performance tuning - Proven solid problem-solving and communication skills
- Ingest and process structured, semi-structured and unstructured data in formats such as CSV, JSON, XML, Parquet, Avro, ORC, Excel and Delta, using Azure Data Factory, Auto Loader and Lakeflow Spark Declarative Pipelines - Develop complex transformations in PySpark and Spark SQL, including CDC, SCD Type 1/2, deduplication and handling of nested or schema-evolving data - Design data models and build the right consumption objects for each use case: managed/external tables, views, temporary views, materialized views and streaming tables
- Experience working with file formats such as CSV, JSON, XML, Parquet, Avro and Delta, including schema inference, schema evolution and nested data handling - Experience with Azure services: ADF, ADLS Gen2, Key Vault, Azure SQL , Power Bi - Solid knowledge of data modeling, ETL/ELT design, Git, CI/CD and Agile delivery
- Databricks Data Engineer Associate/Professional or Microsoft DP-203/DP-700 certification - Experience with Structured Streaming, Kafka/Event Hubs, Lakeflow Jobs and Databricks SQL - Infrastructure as Code experience
Primary Responsibilities: - Design, build and maintain scalable batch and streaming data pipelines on Azure and Databricks using the Medallion Architecture (Bronze, Silver, Gold) on Delta Lake - Ingest and process structured, semi-structured and unstructured data in formats such as CSV, JSON, XML, Parquet, Avro, ORC, Excel and Delta, using Azure Data Factory, Auto Loader and Lakeflow Spark Declarative Pipelines
- Design, build and maintain scalable batch and streaming data pipelines on Azure and Databricks using the Medallion Architecture (Bronze, Silver, Gold) on Delta Lake - Ingest and process structured, semi-structured and unstructured data in formats such as CSV, JSON, XML, Parquet, Avro, ORC, Excel and Delta, using Azure Data Factory, Auto Loader and Lakeflow Spark Declarative Pipelines - Develop complex transformations in PySpark and Spark SQL, including CDC, SCD Type 1/2, deduplication and handling of nested or schema-evolving data
- Tune Spark jobs and Delta tables for performance and cost (partitioning, liquid clustering, Z-ordering, OPTIMIZE/VACUUM, compute sizing) - Drive CI/CD and DataOps practices using Azure DevOps or GitHub, Declarative Automation Bundles and automated testing - Troubleshoot production issues, do root cause analysis and put preventive fixes in place
- B.E./B.Tech./MCA or equivalent degree in Computer Science, IT or Engineering - 6+ years of data engineering experience, including 3+ years hands-on with Azure Databricks - Hands-on experience with Delta Lake, Lakehouse architecture and Unity Catalog
Preferred Qualifications: - Databricks Data Engineer Associate/Professional or Microsoft DP-203/DP-700 certification - Experience with Structured Streaming, Kafka/Event Hubs, Lakeflow Jobs and Databricks SQL
- Build data quality, validation and reconciliation frameworks to keep data accurate and reliable - Tune Spark jobs and Delta tables for performance and cost (partitioning, liquid clustering, Z-ordering, OPTIMIZE/VACUUM, compute sizing) - Drive CI/CD and DataOps practices using Azure DevOps or GitHub, Declarative Automation Bundles and automated testing
- 6+ years of data engineering experience, including 3+ years hands-on with Azure Databricks - Hands-on experience with Delta Lake, Lakehouse architecture and Unity Catalog - Experience working with file formats such as CSV, JSON, XML, Parquet, Avro and Delta, including schema inference, schema evolution and nested data handling
- Exposure to healthcare data (claims, prior authorization, HL7/FHIR, EDI 837/278) and HIPAA compliance - Experience with Power BI or AI/BI dashboards - Experience mentoring or leading a team, or driving cloud migration and modernization

Your next step

Complete your application on careers.unitedhealthgroup.com. The employer’s form will show what is required.

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About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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:

  • Design, build and maintain scalable batch and streaming data pipelines on Azure and Databricks using the Medallion Architecture (Bronze, Silver, Gold) on Delta Lake
  • Ingest and process structured, semi-structured and unstructured data in formats such as CSV, JSON, XML, Parquet, Avro, ORC, Excel and Delta, using Azure Data Factory, Auto Loader and Lakeflow Spark Declarative Pipelines
  • Develop complex transformations in PySpark and Spark SQL, including CDC, SCD Type 1/2, deduplication and handling of nested or schema-evolving data
  • Design data models and build the right consumption objects for each use case: managed/external tables, views, temporary views, materialized views and streaming tables
  • Implement data governance, lineage and security using Unity Catalog, including row/column-level security and PHI/PII protection
  • Build data quality, validation and reconciliation frameworks to keep data accurate and reliable
  • Tune Spark jobs and Delta tables for performance and cost (partitioning, liquid clustering, Z-ordering, OPTIMIZE/VACUUM, compute sizing)
  • Drive CI/CD and DataOps practices using Azure DevOps or GitHub, Declarative Automation Bundles and automated testing
  • Troubleshoot production issues, do root cause analysis and put preventive fixes in place
  • Work with architects, analysts, data scientists and business stakeholders, and mentor junior engineers
  • Use AI-assisted engineering tools to improve development, testing and documentation
  • 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:

  • B.E./B.Tech./MCA or equivalent degree in Computer Science, IT or Engineering
  • 6+ years of data engineering experience, including 3+ years hands-on with Azure Databricks
  • Hands-on experience with Delta Lake, Lakehouse architecture and Unity Catalog
  • Experience working with file formats such as CSV, JSON, XML, Parquet, Avro and Delta, including schema inference, schema evolution and nested data handling
  • Experience with Azure services: ADF, ADLS Gen2, Key Vault, Azure SQL , Power Bi
  • Solid knowledge of data modeling, ETL/ELT design, Git, CI/CD and Agile delivery
  • Good understanding of views, temporary/global temporary views, materialized views, streaming tables and when to use each
  • Solid proficiency in Python, PySpark and SQL, with a solid understanding of Spark internals and performance tuning
  • Proven solid problem-solving and communication skills

 

Preferred Qualifications:

  • Databricks Data Engineer Associate/Professional or Microsoft DP-203/DP-700 certification
  • Experience with Structured Streaming, Kafka/Event Hubs, Lakeflow Jobs and Databricks SQL
  • Infrastructure as Code experience
  • Exposure to healthcare data (claims, prior authorization, HL7/FHIR, EDI 837/278) and HIPAA compliance
  • Experience with Power BI or AI/BI dashboards
  • Experience mentoring or leading a team, or driving cloud migration and modernization

 

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.

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