Hybrid Data Engineer: Pipelines & Analytics

Consumers Energy; Jackson (AL); Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Medical Benefits

Dental Benefits

Vision Benefits

401k with match

Parental Leave

Holiday Pay

Paid Time Off

Educational Assistance

Job summary

Consumers Energy in Michigan is seeking a Data Engineer to collaborate with analytics teams to design, build, and maintain data pipelines and architectures following IT standards. This role supports data warehouses, ETL processes, and data modeling.

You will assemble large datasets, develop ETL solutions, create data visualizations, and help automate data preparation while improving quality and performance.

Qualifications

• Bachelor's degree with 2+ years data engineering experience.
• Experience with ETL, data warehouses, data modeling, and data quality.
• Strong communication and collaboration across teams.

Responsibilities

• Gather and evaluate requirements with data architects and stakeholders.
• Assemble, cleanse, and prepare large datasets from multiple sources.
• Design and develop scalable data pipelines.
• Develop data visualizations and reporting solutions.
• Identify opportunities to automate data prep and transform processes.
• Prepare technical documentation and artifacts.
• Provide technical guidance for design, testing, and implementation.
• Support incident management and production support.
• Perform other duties as assigned.

Skills

Data pipelines

SQL & data modeling

ETL processes

Agile methodologies

Data warehousing

Communication skills

Collaboration

Data quality

Education

Bachelor's degree in CS/ENG/DS

Associate degree

High school diploma/GED

Tools

Databricks

Delta Lake

Delta Live Tables

Unity Catalog

Structured Streaming

Databricks Workflows

Power BI

Job description

Consumers Energy in Michigan is seeking a Data Engineer to collaborate with analytics teams to design, build, and maintain data pipelines and architectures following IT standards. This role supports data warehouses, ETL processes, and data modeling.

You will assemble large datasets, develop ETL solutions, create data visualizations, and help automate data preparation while improving quality and performance.