Prin Data Engineer

Consumers Energy•Jackson, MI

3d•Hybrid

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 Principal Data Engineer is responsible for partnering with diverse analytics teams and business stakeholders across the enterprise to design, develop, and maintain data pipelines and architecture aligned with established IT best practices. Key responsibilities include developing data warehouses; designing, extracting, loading, and testing data solutions; performing data modeling; ensuring application stability; assembling and cleansing large datasets; creating and optimizing ETL processes; and identifying opportunities to automate manual data processes. This role also leads and provides guidance to lower-level Data Engineers, establishing team standards, frameworks, and best practices while ensuring adherence to data engineering principles across analytics teams.

Requirements

Ability to work effectively with contract employees and external vendors.
Knowledge of change and release management tools and processes used to implement solutions across multiple teams and technologies.
Strong understanding of data design principles and systems engineering concepts, including structured design, supportability, scalability, reliability, survivability, and maintainability.
Knowledge of project planning and full lifecycle delivery using Agile methodologies.
Excellent verbal and written communication skills, with the ability to work effectively at all levels of the organization.
Strong ability to establish and maintain effective working relationships across business and IT teams.
Understanding of data testing methodologies and associated tools.
Knowledge of database management principles, including data structures, data modeling, data warehousing, and transaction processing.
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, plus seven (7) or more years of software engineering and intermediate-level data engineering experience, including advanced analytics tool development, data architecture/design, requirements definition, big data pipeline development, ETL processes, data testing fundamentals, and analytic tool deployment best practices.
[OR] Associate’s degree in a related field, plus nine (9) or more years of relevant experience
[OR] High School Diploma, plus eleven (11) or more years of relevant experience.

Nice To Haves

Candidates with one or more of the following skills will stand out:
Ownership of enterprise-level lakehouse architecture, including defining reference architectures, patterns, and guardrails for Databricks platforms at scale.
Recognized expertise in Databricks platform strategy, including governance, workspace/domain strategy, standardization, and team enablement.
Mastery of analytics data modeling standards, including fact/dimension strategies, conformed dimensions, SCD patterns, bridges, and metric governance.
Proven ability to create and enforce engineering standards (e.g., dbt conventions, testing frameworks, documentation standards, code review practices).
Expert-level proficiency in Spark and distributed compute optimization, including guiding teams on design tradeoffs and performance best practices.
Strong experience designing secure, discoverable, self-service data products using catalog, lineage, and access governance principles.
Ability to shape cross-team roadmaps and influence leaders through architecture reviews, decision records, and executive-level recommendations.
Demonstrated leadership in platform reliability and operational excellence, including observability standards, incident response frameworks, resilience practices, and cost optimization.
Experience enabling modern analytics and machine learning practices, including feature-ready datasets, MLflow/MLOps alignment, and experimentation/production workflows.
Recognized ability to mentor and coach technical talent, elevate engineering practices, and scale best practices across an organization.

Responsibilities

Assemble and cleanse large datasets from various sources to support business requirements for enhancements of varying complexity.
Capture and evaluate requirements from data architects and business partners, assess development alternatives, and establish clear delivery timelines.
Create data visualizations to support customer insights, operational efficiency, and other key business performance metrics using a variety of reporting tools.
Identify opportunities to improve internal processes by automating manual data wrangling, optimizing performance, and enhancing data quality.
Prepare documentation and artifacts to support solution delivery and project activities.
Provide day-to-day guidance and mentorship to lower-level Data Engineers to support talent development within the department.
Deliver incident management and technical consulting for current applications and solutions.
Provide technical direction for enhancements of varying scope, including solution alternatives, design, testing, and documentation.
Collaborate with stakeholders and IT partners to design and build efficient data pipelines supporting business and technical requirements.