Data Engineer

Summary

Reporting to the AI & Data Solutions Manager, the Data Engineer will design, build, and maintain scalable data solutions that support reporting, analytics, data governance, and informed decision-making across Covation Global / United Wheels Inc. This role is responsible for developing efficient data pipelines, data models, integrations, and visualization-ready datasets while ensuring data quality, security, reliability, and performance. The Data Engineer will partner closely with Business Intelligence Analyst(s), the Data Governance Team, and IT applications, operations, and web development teams to modernize the company’s data platform and establish consistent development standards, documentation, and data lineage practices.

Experience with AWS data services is strongly preferred and will support the organization’s continued cloud data modernization efforts.

Location:

Miamisburg, OH (HQ)

Department:
Information Technology

Reports To:

AI & Data Solutions Manager

FLSA Status:
Full-Time, Exempt

Level: IC

Travel:
Minimal

Good decisions depend on good data. As Covation Global modernizes its data platform, the Data Engineer is the person who makes trustworthy, well-structured data available to the business — building the pipelines, models, and integrations that turn scattered source systems into reliable reporting and analytics. This role is foundational to the company’s cloud data modernization: it keeps data accurate, secure, and performant, and it gives analysts, governance, and business teams a platform they can build on.

Done well, it accelerates self-service reporting, strengthens data quality and governance, and lets the organization make faster, better-informed decisions across every function.

• Reliable, Scalable Data Pipelines:
  Data pipelines and integrations run reliably and efficiently, extracting, transforming, and loading data from internal and external sources with strong data quality, security, and performance.
• Analytics-Ready Data Platform:
  Well-designed data models, semantic layers, and curated datasets support reporting, dashboards, and self-service analytics, advancing the company’s cloud data modernization on AWS.
• Well-Governed, Well-Documented Data:
  Data quality metrics, validation routines, design documentation, and data lineage practices are maintained, keeping the platform accurate, secure, and aligned with governance and change-management standards.

Other duties may be assigned.

• Model, design, develop, test, and implement backend data structures, reporting datasets, and front-end data solutions to meet business visualization and reporting requirements.
• Design, develop, test, and maintain data pipelines for efficient extraction, transformation, and loading from internal and external data sources.
• Build aggregate data models, dimension views, fact tables, semantic layers, and curated datasets that support analytics and self-service reporting.
• Develop and maintain data integration solutions using SQL, Python, ETL/ELT tools, APIs, and cloud-native data services.
• Support AWS-based data platform capabilities, including storage, transformation, orchestration, compute, and analytics services such as Amazon S3, AWS Glue, Amazon Redshift, AWS Lambda, Amazon RDS, Athena, and related services.

• Maintain the integrity, reliability, security, and performance of company databases and data pipelines.
• Monitor production jobs, provide support for data pipeline failures, remediate issues, and automate routine operational processes.
• Develop data quality metrics, validation…