DTE is one of the nation's largest diversified energy companies. Our electric and gas companies have fueled our customer's homes and Michigan's progress for more than a century.And as Michigan's largest source of renewable energy, we're creating a cleaner, healthier environment to power our future. We're also serving communities beyond Michigan, where our affiliated businesses offer renewable energy, emission control technologies, and energy services to industries in 19 states.
But we're more than a leading energy company... and working at DTE is more than just a job.At DTE, we take great care of each other and our customers, and we use our energy to be a force for growth and prosperity in our communities. When you join us, you'll be part of a team that welcomes, recognizes, and celebrates differences and values everyone's health, safety, and wellbeing. Are you ready to make that kind of difference? Bring your energy to DTE.Together, we can achieve great things.
Testing Required: Not Applicable
Hybrid Role: This role is hybrid, with an established schedule of in-person work required at an assigned work location. Any remote work is expected to be performed from an employee's primary residence, unless allowed (or prohibited) through the Company's remote work guidelines.
Emergency Response: Yes - Must be available to perform a primary assignment in support of DTE's emergency response to storms or other events that impact service to our customers.
Job Summary
Leads data integration and analytics projects that support data collection, automation, transformation, storage, delivery, and reporting processes. Serves as senior advisor for a large business unit or enterprise-level data projects. Optimizes data retrieval and processing, including performance tuning, delivery design for downstream analytics, machine learning modeling (including feature engineering), and reporting. Mentors less-experienced team members. Span of control: 0; individual contributor.
Key Accountabilities
Leads data engineering projects and collaborates with stakeholders to formulate end-to-end solutions, including data structure design to feed downstream analytics, machine learning modeling, feature engineering, prototype development, and reporting
Develops complex data sets and automated pipelines that support data requirements for process improvement and operational efficiency metrics
Designs and implements data process pipelines in on-premise or Cloud platforms required for optimal extraction, transformation, and loading of data from multiple data sources
Builds reporting and visualizations that utilize data pipeline to provide actionable insights into compliance rates, operational efficiency, and other key business performance metrics
Designs and implements effective testing strategies for data pipelines and processing methods
Deploys and automates Machine Learning Models in a data environment (e.g., SQL server, Cloud platform, on-premise servers and machines), including workflow orchestration, scheduling and advanced data processing implementation, and data delivery tools
Educates leaders and other employees on complex data and analytical findings in basic terms and with storytelling and data visualization
Researches and maintains industry best practices for data engineering practices and solutions
Minimum Education & Experience Requirements
This is a dual-track base requirement job; education and experience requirements can be satisfied through one of the following two options:
Bachelor's degree with emphasis on coursework of a quantitative nature (e.g., Computer Science, Mathematics, Physics, Data Science, Econometrics, etc.) and 6years of experience working in a data engineering, data analytical or computer programming function; OR
Master's degree with emphasis on coursework of a quantitative nature (e.g., Computer Science, Mathematics, Physics, Data Science, Econometrics, etc.) and 4 years of experience working in a data engineering, data analytical or computer programming function
PhD degree with emphasis on coursework of a quantitative nature (e.g., Computer Science, Mathematics, Physics, Data Science, Econometrics, etc.) and 2years of experience working in a data engineering, data analytical or computer programming function
Other Qualifications
Preferred Qualifications:
Experience optimizing database, Spark, and Databricks jobs for performance, reliability, and cost, and implementing CI/CD pipelines for data workflows (e.g., Azure DevOps, GitHub Actions).
Strong business domain knowledge with the ability to translate business needs into scalable data and analytics solutions.
Handson experience with cloud platforms (Azure or AWS), including Databricks for scalable, distributed data pipelines.
Other Requirements:
Advanced programming proficiency in SQL and one or more general-purpose languages (e.g., Python, Java).
Advanced experience building and supporting data pipelines for analytics, AI/ML, and GenAI use cases, including feature engineering and modelready datasets.
Experience supporting data infrastructure for agentic AI systems, including autonomous workflows, toolusing agents, and event-driven pipelines.
Advanced proficiency with Big Data platforms, including data extraction, processing, and analytics connectivity.
Advanced proficiency with business intelligence, data blending, and visualization tools (e.g., Microsoft Power Platform, Power BI).
Demonstrated ability to establish and enforce data engineering best practices, including coding standards, architecture, data... For full info follow application link.
DTE Energy is an equal opportunity employer and considers all qualified applicants without regard to race, color, sex, sexual orientation, gender identity, age, religion, disability, national origin, citizenship, height, weight, genetic information, marital status, pregnancy, protected veteran status or any other status protected by law.
