Senior Data Engineer - Information Technology (Kansas City)
Position Summary
We are seeking an accomplished Senior Data Engineer with 8+ years of hands-on experience to join our data team. This role combines deep expertise in data pipeline engineering ETL- SQL Server, Informatica, Active Batch, and SSAS - with strong semantic modeling capabilities, including Power BI and dimensional data modeling. The ideal candidate is equally comfortable supporting and enhancing production pipelines and supporting high-performance analytical models that drive business intelligence across the enterprise.
Key Responsibilities
Pipeline Engineering & Production Support
- Monitor, support, and enhance existing data pipelines built on SQL Server, Informatica, and Active Batch, ensuring high availability and data integrity.
- Develop, maintain, and optimize ETL/ELT processes; troubleshoot performance bottlenecks and data quality issues with minimal downtime.
- Manage and tune Active Batch job workflows for reliable, efficient automation.
- Collaborate with cross-functional teams to resolve data incidents, communicate root cause, and implement preventive measures.
Document pipeline processes, data flows, and technical specifications to support operational continuity and knowledge transfer.
Data Modeling & Semantic Layer
- Design, develop, and optimize SSAS tabular models and lead migration efforts to Power BI semantic models.
- Build and maintain Power BI semantic models leveraging data from SQL Server; ensure high-performance query execution.
- Write, optimize, and troubleshoot SQL, DAX, and Power Query (M) to support analytics and reporting needs.
- Partner with data engineers to design tables and schemas for optimal analytical performance.
- Document data models, business rules, and data mappings using catalog tooling.
- Ensure smooth daily operations of deployed data models; address outages promptly.
Stakeholder Engagement & Mentorship
- Collaborate with business and technical stakeholders to gather requirements and deliver data products aligned to business needs.
- Train and mentor junior engineers and modelers on best practices for pipeline development, data modeling, and optimization.
- Research and recommend tools, methods, and technologies to continuously improve data engineering and modeling practices.