Data Engineer

Consumers Energy•Jackson, MI

30d•Onsite

About The Position

Consumers Energy is Michigan’s largest energy provider, providing natural gas and/or electricity to 6.8 million of the state’s 10 million residents in all 68 Lower Peninsula counties. Consumers Energy knows job number one is to keep the lights on for customers. We are committed to delivering reliable, clean, and affordable energy to our customers 24/7. This position is not eligible for immigration sponsorship, e.g., H-1B, TN, etc. Please do not apply if you will need immigration sponsorship for a work visa now or in the future, including sponsorship for H-1B, TN, etc., now or in the future. We are unable to hire individuals with CPT, OPT, or STEM OPT for this position as the position is not eligible for participation in the H-1B lottery program and is not eligible for current or future immigration sponsorship for a work visa. Location : This position is onsite minimally 3 days a week at One Energy Plaza located in Jackson, MI. The selected candidate must be within a commutable distance or willing to relocate (relocation package is available for those that qualify). 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 Data Engineer is responsible for collaborating with analytic teams and business partners across the enterprise to gather data requirements and design, build, and maintain data pipelines and architecture in alignment with IT best practices. Key responsibilities include developing data warehouses; designing, extracting, and loading data; testing data solutions; performing data modeling; and ensuring the reliability and performance of data applications. The role also involves building analytic tools, preparing and cleaning large datasets, developing ETL solutions using various technologies, creating data visualizations, and identifying opportunities to automate manual data processes. The Data Engineer will seek guidance from Senior and Principal Data Engineers and Data Architects as needed.

Requirements

Ability to work effectively with contract employees and vendors.
Knowledge of change and release tools and processes used to implement solutions across multiple teams and technologies.
Understanding of data design principles and systems engineering concepts, including structured design, supportability, survivability, reliability, scalability, and maintainability.
Knowledge of project planning and full lifecycle delivery within an Agile framework.
Excellent verbal and written communication skills with the ability to work across all levels of the organization.
Strong ability to establish and maintain effective working relationships with both business and IT teams.
Understanding of data testing methodologies and related tools.
Understanding of database management principles, data structures, data modeling, data warehousing, and transaction processing.
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, plus two (2) years of software engineering experience.
Requires beginner-level experience in analytic tool development, data architecture and design, requirements definition, building large-scale data pipelines, ETL tool usage, basic data testing, and analytic tool deployment methodologies.
Associate’s degree in Computer Science, Engineering, Data Science, or a related field, plus four (4) years of software engineering experience, with the same beginner-level experience as outlined above.
High School Diploma, plus six (6) years of software engineering experience, with the same beginner-level experience as outlined above.

Nice To Haves

Candidates with one or more of the following skills will stand out:
Proficiency in building and operating pipelines in Databricks (Jobs/Workflows, parameterization, cluster policies, reusable libraries).
Strong Python engineering skills for data (modular development, packaging patterns, logging, error handling, performance optimization).
Solid Spark/PySpark experience (join strategies, partitioning, caching, skew mitigation, incremental processing).
Experience designing dimensional models (facts/dimensions, conformed dimensions, SCD patterns, bridge tables).
Proficiency with dbt (macros, snapshots, tests, documentation, exposures, CI integration, model refactoring).
Experience implementing lakehouse/data architecture patterns (bronze/silver/gold layers, data product concepts, semantic consistency).
Familiarity with governance and cataloging concepts (e.g., Unity Catalog-style organization, workspace/domain separation principles).
Strong SQL skills for transformation and optimization (window functions, CTEs, query tuning).
Experience connecting curated datasets to consumption tools (e.g., Power BI integration).
Comfort working in Agile delivery environments and producing clear technical documentation and artifacts.

Responsibilities

Assemble and clean large datasets from multiple sources to support functional business requirements for small to large enhancements.
Capture and evaluate requirements from Data Architects or business partners, assess development alternatives, and establish timelines.
Create data visualizations that support customer insights, operational efficiency, and key business performance metrics using various reporting tools.
Identify opportunities to enhance internal processes, automate manual data tasks, optimize performance, and improve overall data quality.
Prepare artifacts that support proposed solutions and document project activities.
Provide incident management and technical consulting support for existing applications and solutions.
Offer technical guidance for enhancements of varying complexity, including solution alternatives, design, testing, and documentation.
Partner with stakeholders and IT teams to design and develop efficient data pipelines for enhancements of all sizes.
Perform other duties as assigned or as necessary.