Senior Data Engineer

Senior Data Engineer (Detroit, MI - Hybrid)

Optomi, in partnership with a leading Fortune 500 organization, is looking for a Senior Data Engineer to join their growing team in Detroit, MI! This is an exciting opportunity for an experienced Data Engineer to help design, build, and optimize enterprise-scale data pipelines and cloud data platforms that power analytics, reporting, and AI/ML initiatives across the organization.

What the right candidate will enjoy:

• Hybrid opportunity based out of Detroit, MI!
• Building scalable cloud-native data pipelines using Snowflake, AWS, and Python!
• Working on enterprise data platforms that support analytics, reporting, and AI/ML initiatives!
• Collaborating with Data Science, BI, Product, and Platform teams to deliver AI-ready datasets and modern data solutions!
• Joining a collaborative Agile team focused on modernizing enterprise data architecture and solving complex data engineering challenges!

Experience the right candidate will have:

• 9+ years of hands-on Data Engineering experience building enterprise-scale data platforms.
• Strong experience with Snowflake, including data modeling, SQL development, performance tuning, and best practices.
• Hands-on experience developing ETL/ELT pipelines using Python and AWS services such as S3, Glue, Lambda, EMR, Step Functions, or CloudWatch.
• Experience with enterprise scheduling and orchestration tools such as Control-M.
• Experience building or supporting IBM DataStage ETL workflows in enterprise environments.
• Strong SQL skills with experience optimizing queries and validating large datasets.
• Experience with Git, CI/CD, and production support within Agile development environments.
• Excellent communication skills with the ability to collaborate across engineering, analytics, and business teams.

Responsibilities of the right candidate:

• Design, develop, and maintain scalable batch and near real-time data pipelines using Snowflake, AWS, and Python.
• Build and optimize Snowflake data models that support enterprise analytics, reporting, and downstream data consumers.
• Develop, maintain, and modernize ETL/ELT workflows using Python and IBM DataStage.
• Manage enterprise job scheduling, monitoring, dependencies, and production support using Control-M.
• Ensure data quality, governance, lineage, documentation, and operational best practices across enterprise data pipelines.
• Optimize Snowflake and AWS performance through query tuning, warehouse optimization, and cost management.
• Partner with Data Science, BI, Product, and Platform teams to deliver trusted, AI-ready datasets.
• Participate in Agile ceremonies, sprint planning, and SDLC processes while supporting continuous delivery.
• Troubleshoot production issues, perform root cause analysis, and implement long-term improvements to increase platform reliability.