Sr Data Engineer

Consumers Energy•Jackson, MI

3d•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 Senior Data Engineer works independently with minimal direction and is responsible for partnering with analytics teams and business stakeholders across the enterprise to gather data requirements and design, develop, and maintain data pipelines and data architecture in alignment with IT best practices. Responsibilities include developing data warehouses, designing extraction and loading processes, performing data modeling, testing solutions, and ensuring the reliable operation of data applications. The role also includes building analytical tools, assembling and cleansing large datasets, designing and implementing ETL solutions, creating data visualizations, and identifying opportunities to automate manual processes to enhance performance and improve data quality.

Requirements

Excellent verbal and written communication skills with the ability to collaborate effectively at all organizational levels.
Demonstrated ability to build and maintain strong working relationships with both business and IT teams.
Knowledge of project planning and full lifecycle delivery methodologies, particularly within Agile frameworks.
Understanding of data testing methodologies and related testing tools.
Ability to work effectively with contractors and vendor partners.
Strong understanding of database management principles, including data structures, data modeling, data warehousing, and transaction processing.
Knowledge of data design principles and systems engineering concepts such as structured design, supportability, survivability, reliability, scalability, and maintainability.
Familiarity with change management and release processes used for implementing solutions across multiple teams and technologies.
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, plus four (4) or more years of software engineering experience as an Intermediate Data Engineer, including experience in advanced analytic tool development, data architecture/design, requirements gathering, big data pipeline development, ETL extraction, basic data testing, and analytic tool deployment best practices [OR] Associate’s degree in a related field, plus six (6) or more years of relevant experience [OR] High School Diploma, plus eight (8) or more years of relevant experience.

Nice To Haves

Advanced expertise with Databricks, including multi-workspace patterns, orchestration strategies, performance optimization, and reliability engineering.
Deep proficiency in Apache Spark, including structured streaming, incremental processing frameworks, advanced tuning, cluster sizing, and runtime optimization.
Strong data architecture leadership, including designing scalable lakehouse domains, defining enterprise standards, and aligning patterns with business outcomes.
Expert-level dimensional modeling experience, including SCD handling, conformance strategies, metric standardization, and semantic layer design.
Production-grade dbt experience, including project structure, performance optimization, testing strategies, documentation enforcement, and CI/CD practices.
Experience implementing data quality and observability frameworks (SLAs/SLOs, freshness checks, anomaly detection, incident runbooks).
Strong understanding of governance practices such as data cataloging, access workflows, lineage management, and secure self-service enablement.
Demonstrated ability to mentor engineering teams, define coding standards, and lead design reviews.
Experience collaborating with data scientists or analytics teams to operationalize datasets and support machine learning feature development.
Proven track record of improving internal processes through automation, performance optimization, and enhanced data reliability.

Responsibilities

Assemble and cleanse large and complex datasets from various sources to meet business requirements for medium to large enhancements, IT projects, or technical modeling initiatives.
Build analytic tools that leverage data pipelines to provide actionable insights into customer acquisition, operational efficiency, and other key performance metrics.
Capture and evaluate requirements from data architects and business partners, assess development alternatives, and establish project timelines.
Design and create advanced data visualizations using various reporting tools to support customer insights, operational dashboards, and business performance metrics.
Identify and enhance internal processes by automating manual data preparation tasks, optimizing performance, and improving data quality for medium to large enhancements and IT or modeling projects.
Prepare, review, and/or approve technical artifacts to support deployed solutions and document development activities.
Provide technical expertise for solution design, testing, and documentation on medium to large enhancements and IT or modeling projects.
Offer technical leadership for incident management and provide consulting and support for existing applications and solutions.
Collaborate with stakeholders and IT teams to design and build efficient data pipelines supporting enterprise initiatives.