Data Engineer

Salary: $72,800 - 130,000 per year Requirements:

• We require 3+ years of experience in data engineering, including designing and implementing data pipelines and ETL workflows, with familiarity in incremental loads and change data capture (CDC).
• We require 2+ years of experience with SQL for data manipulation and query optimization, along with Python and Apache Spark/PySpark for efficient batch and streaming transformations.
• We require 1+ years of experience working with Azure, Databricks, or a comparable cloud data platform, including cluster management, notebooks, and Delta Lake or Parquet.
• We require experience working in agile team environments and communicating clearly with both technical and non-technical partners.
• We require comfort with version control and collaborative development practices such as code reviews and pair programming when needed.
• We require familiarity with streaming technologies such as Spark Streaming, Kafka, or Azure Event Hubs for real-time ingestion.
• We require proven ability to identify and resolve data issues, including data stoppages, schema changes, and validation failures.
• We prefer experience with declarative pipeline frameworks or workflow tools such as Databricks Delta Live Tables.
• We prefer experience embedding data quality checks into pipelines and familiarity with security, encryption, and sensitive data handling.
• We prefer hands-on skill in Spark or SQL performance tuning, including partitioning, caching, and troubleshooting shuffle bottlenecks.

• We design, build, and maintain scalable, reliable data pipelines that support both batch and real-time analytics in our Azure-based platform.
• We ingest data from diverse sources using Azure Data Factory and PySpark in Databricks, and we set up streaming and batch ETL processes for recurring loads.
• We apply Medallion architecture practices by capturing raw data in bronze, transforming and cleansing it in silver, and curating analysis-ready gold datasets.
• We tune Spark jobs, improve query logic, and manage resources to maximize throughput, reduce latency, and control costs.
• We integrate data from APIs, databases, file feeds, IoT streams, and other sources while handling missing, corrupt, or inconsistent records.
• We implement validation rules, automated checks, and alerting to detect data quality issues early across batch and streaming pipelines.
• We evaluate and adopt emerging tools such as Delta Live Tables or Lakehouse-style pipeline frameworks where appropriate.
• We monitor pipeline health, investigate failures or delays, identify root causes, and implement durable fixes.
• We collaborate closely with other data engineers and data science and reporting partners to align on evolving data needs.
• We document pipeline logic, source and destination schemas, lineage, and governance controls, including privacy, masking, encryption, and access management.

• Azure
• Cloud
• Databricks
• ETL
• IoT
• Support
• Kafka
• Python
• PySpark
• SQL
• Security
• Spark
• Machine Learning

More:

We are UnitedHealthcare, part of UnitedHealth Group, and we are focused on simplifying the health care experience, building healthier communities, and removing barriers to quality care. This is a remote role open to candidates anywhere within the U.S.; if you are based in the Minneapolis or Washington, D.C. area, you will be expected to work in the office at least four days per week. We offer a competitive salary range of $72,800 to $130,000 annually, along with a comprehensive benefits package, incentive and recognition programs, equity stock purchase, and a 401k contribution, subject to eligibility. We are committed to health equity, inclusive care, environmental responsibility, and an equal opportunity workplace. Employees working remotely must follow our Telecommuter Policy, and candidates must pass a pre-employment drug test.

last updated 33 week of 2026