Data Engineer - Emergency Preparedness and Response

Job Summary

Counsels data integration and analytics projects that automate data collection, transformation, storage, delivery, and reporting processes. Ensures optimization of data retrieval and processing, including performance tuning, delivery design for down-stream analytics, machine learning modeling, feature engineering, and reporting.

Key Accountabilities

• Facilitates 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
• Works with business units, data architects, cloud engineers, and data scientists to identify relevant data, analyze data quality, design data requirements, and develop prototypes for proof-of-concepts
• Develops 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
• Buils 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 automation and 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

Minimum Education & Experience Requirements

• 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 3 years of experience working in a data engineering, data analytical, or computer programming function;
• Master’s degree with emphasis on coursework of a quantitative nature (e.g., Computer Science, Mathematics, Physics, Data Science, Econometrics, etc.) and 1 year of experience working in a data engineering, data analytical, or computer programming function.

Preferred Qualifications

• Experience with cloud platforms and cloud commuting concepts (e.g., Azure)
• Business domain knowledge
• SQL Database design and query optimization experience
• Advanced business acumen
• Experience with utility/energy industry
• Knowledge of DTE’s ADMS Outage Management System and business processes
• Proficiency in SQL, including writing efficient queries and supporting basic data model or schema design
• Intermediate programming skills in a modern language such as Python, C#, Java, or R to support data transformation and automation
• Hands‑on experience building and maintaining data pipelines using cloud‑based platforms (e.g., Azure data services such as Data Factory, Databricks, or equivalent)
• Experience supporting analytics and reporting use cases using BI and data visualization tools (e.g., Power BI / Microsoft Power Platform)
• Experience integrating data from multiple source systems with attention to data quality and reliability
• Demonstrated proficiency in developing or deploying artificial intelligence models
• Demonstrated examples of written and oral communication skills such as oral presentations, detailed status reports and training delivery