Industrial Electric Mfg. (IEM) is the largest independent full-line manufacturer of custom power distribution systems in North America. The role involves building dashboards and serving as a thought partner to engineering leadership, ensuring data quality and providing insights into operational performance.
Responsibilities:
- Be a thought partner, not an order-taker. Work directly with Engineering leadership and team leads to understand the operational problems they're trying to solve - then figure out what data is needed, whether it exists, whether it's accurate, and what it means
- Diagnose, don't just report. When scheduling backlogs are growing, or mechanical lead times spike for certain product lines, or change notice on-time rates are lagging; your job is to get to the bottom of it, not hand back a chart and say, "that's what the data shows."
- Clean up the data foundation. Work hands-on with SMEs across ERP, HR systems, engineering milestone tracking, and drawing review systems to identify data quality issues, misaligned definitions, and gaps that undermine confidence in the numbers. Fix them, document them, and prevent them from recurring
- Instrument the engineering process end-to-end. Track pipeline health, engineering phase lead times, and per-engineer performance metrics with enough context that leadership understands the drivers, not just the outputs
- Support mechanical design operations. Give the mechanical team real-time visibility into scheduling KPIs; open order value, late orders, upcoming due dates, drawing review throughput, and help them understand what's causing delays when they occur
- Build and maintain Tableau dashboards that give engineering teams what they need at the right level of detail - executive scorecards, operational queue views, and order-level drill-throughs - with the analytical narrative baked in, not left for the reader to guess
- Work with data engineering to develop Snowflake/dbt data models that integrate ERP order data, HR workforce data, and engineering milestone data into a clean, trustworthy analytical layer that the team can build on
Requirements:
- 3+ years of BI or analytics experience in a manufacturing environment - engineer-to-order or make-to-order strongly preferred
- Demonstrated experience working across multiple source systems and with the SMEs who own them, including getting into data quality issues, reconciling definitions, and building trust in the numbers before building dashboards on top of them
- Analytical depth, not just visualization skill. You can take a metric that looks wrong, form a hypothesis about why, pull the data to test it, and communicate a clear finding to a non-technical stakeholder
- Consultative instincts. You push back when the question being asked isn't the right question. You surface what leadership needs to know, not just what they asked for
- Advanced Tableau, strong SQL, and familiarity with Snowflake and dbt or a demonstrated ability to get there fast
- Background in electrical or mechanical engineering, or years of embedded experience working inside engineering teams, is heavily weighted in our evaluation
- Bachelor's degree in Data Analytics, Engineering, Computer Science, or a related field