Senior Data Engineer
Senior
Azure Data Factory
Big Data
Bigdata
Cloud Operations
Cloud Platform
Data
Data Engineer
Data Integration
Data Pipeline
Data Platform
Data Processing
Data Warehouse
Data Warehousing
Database
Databases
Databricks
ETL
Informatica
Information Technology (IT)
Microsoft Azure
Oracle
Programming Language
Programming Languages
Snowflake
SQL
Teradata
Job Description
The Senior Data Engineer role at Optum focuses on designing, developing, and maintaining enterprise ETL pipelines for Medicaid analytics and the enterprise data warehouse, leveraging Azure, Python, Spark, and cloud data technologies.
Location and Compensation
Location: Eden Prairie, MN (remote). Salary: USD 91,700 - 163,700 per year.
Responsibilities
- Design, develop, and maintain enterprise ETL pipelines using Azure Data Factory, Informatica PowerCenter, and Python-based frameworks
- Build and optimize scalable data processing solutions with Python, Spark, and Databricks
- Support Medicaid analytics and federal reporting initiatives (T MSIS, PERM, MARS, Quality of Care)
- Develop robust data validation, reconciliation, and auditable data pipelines
- Write and optimize SQL and stored procedures across relational platforms such as Snowflake, Oracle, and SQL Server
- Participate in cloud migration and modernization initiatives within Azure-based architectures
- Collaborate with analysts, QA, and reporting teams to ensure data quality, accuracy, and timeliness
- Follow data engineering best practices for performance, reliability, reusability, and security
- Support production operations, incident resolution, and root cause analysis
- Participate in code reviews, source control, and CI/CD processes using Azure DevOps and GitHub
Requirements
- 5+ years of data engineering experience with a focus on enterprise data warehousing
- 5+ years of hands-on ETL development using Informatica PowerCenter, Azure Data Factory, or similar tools
- 5+ years of Python development for data engineering and automation
- 5+ years of Teradata experience
- 3+ years of experience with Spark based processing frameworks (Databricks or equivalent)
- Solid SQL expertise and experience with relational databases (such as Snowflake, Oracle, SQL Server)
- Experience with source control and DevOps practices (Azure DevOps, GitHub, CI/CD)
- Proven solid analytical, problem solving, and troubleshooting skills
- Ability to travel periodically based on project or customer needs
Technologies
- Python
- Azure Data Factory
- Informatica PowerCenter
- Spark
- Databricks
- Azure
- Snowflake
- Oracle
- SQL Server
- Teradata
- Azure DevOps
- GitHub
- CI/CD
- PowerShell
- Bash
- REST API
Benefits
- Comprehensive benefits package
- Incentive and recognition programs
- Equity stock purchase
- 401k contribution
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