Data Engineer (Databricks, Python, Azure)

Data Engineer (Databricks, Python, Azure)

Optomi, in partnership with a leading energy provider serving communities throughout Michigan, is seeking an experienced Data Engineer to join their team! This organization plays a critical role in delivering reliable energy while investing in modern technology, automation, analytics, and more sustainable energy solutions. The ideal candidate will bring hands-on experience building scalable data pipelines, ETL/ELT solutions, data models, and data quality processes, along with the ability to collaborate cross-functionally with business stakeholders, Data Architects, Data Analysts, and IT professionals.

What the right candidate will enjoy!

• Hybrid position! (Ability to work partly remote once established)
• Working on data engineering initiatives that support a key service and have a tangible impact on customers across Michigan!
• Building and improving modern data solutions using Databricks, Delta Lake, Lakehouse Architecture, and other modern data engineering tools.
• Joining a company recognized in 2025 as the “Best Place to Work for Disability Inclusion”, with initiatives designed to foster diversity and belonging.
• Having opportunities to continue developing technically through structured career-development programs and technical training.
• Being part of an organization with a strong emphasis on community involvement, with employees volunteering with nonprofits and communities throughout Michigan.

Experience of the right candidate:

• 2+ years of professional experience in Data Engineering or Software Engineering with a Bachelor's degree in Computer Science, Engineering, Data Science, or a related field; equivalent experience may be considered.
• Strong hands-on experience designing and building scalable data pipelines and ETL/ELT solutions with various data sources.
• Experience working with Databricks, with experience in Delta Lake, DLT, Databricks Workflows, Unity Catalog, Structured Streaming, or Lakehouse Architecture strongly preferred.
• Working knowledge of Medallion Architecture and modern data engineering practices.
• Strong experience with data modeling, including designing and implementing star-schema models.
• Experience working with large and complex datasets, including data extraction, cleansing, and transforming for analytics.
• Experience developing data quality frameworks and maintaining them.
• Experience with CI/CD pipelines and DevOps practices supporting data engineering development, deployment, and operational efficiency.
• Understanding of database management, data warehousing, data structures, data design, scalability, reliability, maintainability, and supportability.
• Experience working within Agile software development environments and across the SDLC.
• Strong communication skills with the ability to work effectively alongside technical teams, business stakeholders, contractors, and consultants.

Responsibilities of the right candidate:

• Gather and evaluate data requirements from Data Architects, business stakeholders, analytics teams, and IT partners.
• Design, develop, maintain, and optimize scalable data pipelines and ETL/ELT solutions.
• Gather, cleanse, transform, and prepare large and complex datasets from multiple data sources for analysis.
• Develop and maintain data warehouses, data models, analytical tools, and reporting solutions.
• Design data solutions that support business analytics, operational efficiency, and key business performance metrics.
• Identify opportunities to automate manual data preparation and transformation processes.
• Improve data quality through testing, validation, monitoring, and data quality frameworks.
• Optimize data solutions for performance, reliability, scalability, and maintainability.
• Collaborate with business partners, Data Architects, analytics teams, and IT professionals to turn business requirements into technical solutions.
• Provide technical guidance throughout solution design, testing, documentation, implementation, and deployment.
• Develop technical documentation and project artifacts supporting solution development and delivery.
• Support CI/CD, deployment, release management, and production support activities.
• Participate in incident management and troubleshoot existing data applications and solutions.
• Develop data visualizations and reporting solutions that provide customer insights, operational efficiencies, and business performance metrics.