Jobs
Jobs
Data Engineer
Summary
Be part of building the tech that maintains the largest machine on earth—the U.S. power grid. Associated Electric owns and operates a fleet of power plants powering homes across the Midwest, and we’re building a new product that will become the backbone of how Associated Electric Cooperative manages those power plants. This product will become the digital twin of our entire power plant fleet — used across the organization, from the plant floor to company leadership — giving everyone a shared, data-driven view of plant health and performance. It will unite asset data, financials, and strategic plans into one integrated platform that aligns daily operations with long-term strategy.
To build this product, we need you — an engineer with deep data and modeling experience — on our Plant Asset Management Technology team. You’ll join us on the ground floor of this new technology movement, shape the product, and work side-by-side with business stakeholders and software engineers to create something that matters. This will be a product that changes the game for its users, drives bottom-line impact for the company, and stands as a lighthouse example for the industry on how to make technology transform how we manage some of the most complex and critical assets in existence.
You and your team won’t be starting from scratch — the team already has full product management ownership of an ecosystem of power production technology systems that will integrate with this new product. Some are third-party systems, like our newly modernized enterprise asset management platform, and others are smaller 3rd or first-party tools that may be modernized or replaced as the new product the team is building comes online. Being part of supporting and evolving this ecosystem means that you’ll have ample opportunity to know your users, run and improve the current systems, and chart the future for each product in a world where the digital twin becomes the hub of plant management.
Responsibilities
What you’ll do:
- Own the Data Design: Architect lakehouse models and pipelines that bring together telemetry from thousands of sensors and devices with work management and financial data. Build the data mart and semantic model that power user-driven analytics.
- Build the Digital Twin: Design the high-level models that integrate asset-level predictive models with financial, work management, and operational data to create a true fleet-wide picture of health, risk, and performance. Work with business teams managing asset models to ensure they can connect seamlessly into the digital twin.
- Fuse the Enterprise: Integrate financial perspectives into reliability and lifecycle models, Continually find ways to bring in additional operational, planning, and maintenance systems to enrich the digital twin.
- Build for the Users: Champion the people who rely on this product — from plant floor staff to executives. Relentlessly look for better ways to capture, model, and deliver insights, and connect them to the information they need to make faster, smarter decisions.
- Ship! Ship! Ship! Work with PM, UX, software engineers, and expert stakeholders to turn data, models, and visuals into a web app that users can’t wait to adopt. Champion design, value, and quality so every release makes the product stronger.
How we build:
You’ll work in a small, empowered agile product team with a dedicated Product Manager (your direct lead), UX designer, software engineers, and analysts — shipping fast, learning fast, and building toward a bigger vision. You’ll collaborate daily to turn data and models into a web-based product that delights users, while iterating closely with plant staff and executives to ensure it works in the real world. You’ll build on a cloud-first Microsoft stack — Azure, Databricks (Delta Lake), Azure SQL, Cosmos DB, Azure Web Apps, Python/C#. Importantly, you’ll have leadership support and a mandate to deliver something that makes a lasting difference.
Experience Requirements
What you’ll need:
- Education & Core Skills: A bachelor’s degree in a STEM field (or equivalent experience) with a strong foundation in data engineering, system design, and enterprise integration patterns.
- Modern Data Engineering Expertise: Proficiency with ETL/ELT frameworks, SQL/NoSQL, and cloud-based data platforms — especially Microsoft Azure (Storage Accounts, SQL Databases, Synapse Analytics, Data Factory, Data Lake, Delta Lake).
- Data Architecture: Deep understanding of how to design data architectures that power analytics and data science operations — including data modeling, star schemas, semantic layers, and decoupled system integration patterns that scale across the enterprise and support ML/AI workloads.
- Model Engineering: Build and evolve the high-level Databricks models that power the digital twin, combining financial, operational, and reliability data. Support business teams by integrating their asset-level models into fleet-wide views and ensuring they connect seamlessly into the larger platform.
- Data Visualization Mastery: Ability to design visualizations for clarity and density, building visual dashboards, charts, and tools that expert users can quickly and capably use to see insights and perform deep analytics. Familiarity with best practices (e.g., Stephen Few’s work) is a big plus.
- Programming & Automation: Comfort with scripting or programming (Python or similar) to automate pipelines and integrate with downstream systems — bonus points if you can speak the language of software engineers and help guide how data integrates into the UI.
- Business Mindset: Ability to understand business processes, see the “why” behind requirements, and shape solutions that improve how the business runs — connecting technical decisions to business value.
- Collaboration & Influence: Excellent communication skills, able to navigate technical and business discussions, align diverse teams, and lead initiatives without formal authority.
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