Remote Data Engineer — AI-Driven Health Analytics

Optum; Eden Prairie (MN); Remote; USD 60,000 - 107,000; Full time

Benefits offered by this job

Comprehensive benefits package

Incentive and recognition programs

Equity stock purchase plan

401k contribution

Job summary

Optum is seeking an Associate Data Engineer to design, build, and maintain scalable data pipelines and storage solutions. You will collaborate with data scientists and analysts to support analytics, while embedding enterprise AI tools to streamline workflows and drive efficiency across healthcare data solutions.

You will work on real-time data ingestion with Kafka and batch processing with Spark, using AWS Athena for analysis, and contribute to documentation and governance across multiple data

Qualifications

• 2+ years of data engineering and SQL/ETL experience.

Responsibilities

• Develop and maintain data pipelines for EiMP consolidating data from multiple sources.
• Support real-time ingestion with Kafka and batch processing with Spark.
• Analyze data using AWS Athena to support business needs.
• Generate reports and dashboards to provide insights.
• Ensure data quality and governance across sources.
• Collaborate with data scientists and analysts to deliver solutions.
• Document data pipelines and processes.
• Support ad hoc data requests.

Skills

Data engineering

SQL

ETL tools

Cross-functional collaboration

Troubleshoot pipelines

AI / prompt engineering

Education

Bachelor's degree in Computer Science or related field

Tools

Apache Spark

Apache Kafka

AWS Athena

Job description

Optum is seeking an Associate Data Engineer to design, build, and maintain scalable data pipelines and storage solutions. You will collaborate with data scientists and analysts to support analytics, while embedding enterprise AI tools to streamline workflows and drive efficiency across healthcare data solutions.

You will work on real-time data ingestion with Kafka and batch processing with Spark, using AWS Athena for analysis, and contribute to documentation and governance across multiple data