Data Engineer

• Title: Data Engineer
• Location: Remote but must live within 2 hours of New Bremen, OH (will come onsite 1 day a quarter)
• Salary: 90K-120K

We are seeking a Data Engineer to develop, enhance, and support modern data products and analytics platforms. This individual will work across SQL-based data engineering, data modeling, ETL/ELT pipelines, CI/CD automation, and business intelligence enablement.

The ideal candidate understands not only how to build data models, but also why specific modeling approaches work and when to apply them. This person will partner closely with data analysts, BI developers, business analysts, quality analysts, and operations teams to deliver dependable, scalable, and well-documented data solutions.

This is an excellent opportunity for a hands-on data engineer who has a strong SQL foundation and wants to work across technologies such as Microsoft Fabric, Starburst, Trino, dbt, Kafka, CDC, Debezium, Python, and Power BI.

• Key Responsibilities
• Develop, enhance, and support data products using SQL and Python.
• Design and maintain ETL and ELT pipelines for structured and analytical data.
• Support streaming and change-data-capture solutions using Kafka, CDC, and Debezium.
• Build and maintain CI/CD workflows for data platform pipelines and applications.
• Develop solutions on Starburst and Trino using a dbt-based development framework.
• Build and support data solutions within Microsoft Fabric.
• Create scalable, maintainable data models that support reporting, analytics, and Power BI use cases.
• Partner with data analysts and BI developers to establish best practices for data modeling and Power BI consumption.
• Participate in peer code reviews to improve code quality, consistency, maintainability, and knowledge sharing.
• Analyze dependencies among applications, pipelines, datasets, and source systems to identify downstream impacts before changes are released.
• Partner with business analysts to document technical and functional requirements.
• Prepare technical specifications, support documentation, data-flow documentation, and programming documentation in accordance with internal standards.
• Provide knowledge transfer to Support and Operations teams when systems or processes change.
• Work with quality analysts to ensure changes are thoroughly tested before release.
• Write unit and integration tests for newly developed code.
• Assist with troubleshooting, root-cause analysis, application testing, and production support.
• Stay informed about changes and advances in data engineering, cloud platforms, distributed query engines, and software development practices.
• Lead or coordinate smaller data initiatives as experience permits.

• Required Qualifications
• Bachelor’s degree in Computer Science or a related technical field.
• Strong professional SQL experience, including the ability to develop, troubleshoot, and optimize complex queries.
• Demonstrated understanding of data modeling principles.
• Ability to explain why different data modeling approaches work and identify the appropriate approach for a given analytics or operational use case.
• Experience developing or supporting ETL/ELT pipelines.
• Understanding of software development lifecycle practices, source control, testing, and production deployment.
• Strong analytical and problem-solving skills.
• Ability to communicate effectively with both technical and business stakeholders.

• Preferred Qualifications
• Professional Python experience.
• Experience with one or more of the following:
• Microsoft Fabric
• Starburst
• Snowflake
• Databricks
• Trino
• Experience using dbt for data transformation, testing, documentation, or deployment.
• Experience with Kafka or event-driven data pipelines.
• Experience implementing change data capture, ideally using Debezium.
• Experience creating CI/CD workflows for data pipelines or applications.
• Experience supporting Power BI datasets, semantic models, or reporting teams.
• Experience performing code reviews.
• Experience leading smaller projects, technical workstreams, or platform enhancements.
• Familiarity with unit testing and integration testing for data solutions.

What Success Looks Like

A successful candidate will be able to:

• Quickly understand the organization’s data ecosystem and system dependencies.
• Build reliable SQL-based data products and pipelines.
• Apply sound data modeling practices rather than simply moving data between systems.
• Help analysts and BI developers use governed, reusable data structures.
• Improve code quality through testing, documentation, and code review.
• Become productive in Microsoft Fabric and the Starburst/Trino/dbt environment.
• Communicate implementation risks, downstream impacts, and technical decisions clearly.