Sr Data Analyst

General Summary of Job Responsibilities

The Applications and Analytics team is at the heart of innovation, powering Michigan's future by crafting cutting‑edge digital solutions that transform how our customers and communities experience energy. Guided by our Digital First strategy, we harness modern technical practices and agile methodologies to ensure data and insights are accessible, reliable, and actionable, enabling evidence‑based decision‑making, operational efficiency, and innovation across the organization.

Join a dynamic team where collaboration, creativity, and impact converge!

We partner closely with business teams to uncover digital opportunities, prioritize high‑impact outcomes, and deliver trustworthy, user‑friendly technology. By embracing our CE Way principles—engaging on solutions, illuminating priorities, and minimizing waste—we build systems that are simple, helpful, and valuable. If you're passionate about innovation, community, and shaping a sustainable energy future, come grow with us at Consumers Energy!

The Senior Data Analyst plays a critical role in developing, enhancing, and maintaining standardized company data models. This position requires familiarity with at least one data domain and subject‑matter expertise within a specific business area. The Senior Data Analyst serves as a mentor to team members and brings strong technical expertise to ensure the accuracy, quality, and usability of data. They transform, design, and present data in ways that support informed decision‑making across the organization.

This role is responsible for delivering timely, high‑quality reporting that supports business strategies. It also requires coordination across multiple stakeholders and may involve assuming project‑management responsibilities to lead teams or large initiatives.

• Collaborates with departments across the organization to identify data needs, goals, and objectives.
• Identifies trends and patterns in data and provides recommendations for improvement, optimization, and new value opportunities.
• Applies knowledge of data and its interaction with applications to troubleshoot issues, analyze root causes, and recommend solutions.
• Collects, cleans, and analyzes data from multiple sources using statistical methods and tools such as SQL, Python, R, and Excel.
• Communicates insights to leadership and other stakeholders through presentations, reports, dashboards, and visualizations.
• Performs statistical analysis and interprets results from advanced analytical techniques.
• Supports data investigations and analytical needs for departmental initiatives.
• Performs other duties as assigned.

• Ability to analyze and interpret data to support informed decision‑making.
• Ability to present findings to diverse audiences, both technical and non‑technical.
• Ability to identify, analyze, and solve a wide range of problems.
• Ability to understand both the big picture and the detailed components of data initiatives.
• Excellent written and verbal communication skills.
• Knowledge of statistical analysis, data visualization, and an understanding of data modeling and data engineering concepts.

• Bachelor's degree in Information Technology, Data Analytics, or a related field, with four (4)+ years of experience transforming data into meaningful insights, presenting to business stakeholders, and driving business value.
  
  Experience with data and information management and hands‑on work with Big Data/No
  
  SQL platforms at production scale.
  • [OR] Associate's degree in Information Technology, Data Analytics, or a related field, with six (6)+ years of relevant experience as described above.
  • [OR] High School Diploma, with eight (8)+ years of relevant experience as described above.

Candidates with one or more of the following skills will stand out:

• Familiarity with Databricks and its analytical capabilities.
• Strong understanding of dimensional modeling concepts (fact tables, dimensions, star schema) and their role in analytics.
• Proficiency in writing complex SQL queries, including joins, aggregations, and window functions.
• Experience cleaning, transforming, and preparing datasets using tools such as Python.
• Ability to design clear, impactful dashboards and visualizations using Tableau, Power BI, or visualization libraries.
• Advanced Excel/Google Sheets skills, including pivot tables, lookups, and complex formulas.
• Expertise in developing KPIs, metrics, and data‑driven recommendations that support business objectives.