Senior Data Engineer

 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 6 years 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 2 years 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 perfo