Data Engineer

Kimball Midwest•Worthington, OH

20h•Onsite

About The Position

Kimball Midwest, a national distributor of maintenance, repair, and operation products, is searching for a Data Engineer to join our IT team! We are looking for someone who is driven, passionate about data and technology, and excited about the future of Microsoft Fabric. This role requires a leader who stays up-to-date on technology trends, brings new ideas to the table, and thrives in a collaborative team environment within a Microsoft ecosystem. As a Kimball Midwest associate, you will experience why we have been recognized as one of the Top Workplaces in Columbus thirteen years in a row! Our sales revenue growth is dynamic, increasing from $1 million in 1983 to over $500 million today. Throughout all our growth we have kept the family-owned and operated culture alive. At Kimball Midwest, you are a name and not a number and we pride ourselves on our unique culture.

Requirements

5+ years of experience in data engineering or a related field.
Bachelor’s degree in Computer Science or equivalent experience.
Proven passion for data and technology, with a record of continuous learning and leadership.
Expertise in tools and languages: Python, SQL, Azure Synapse Analytics, Microsoft Fabric (Lakehouse, Dataflows), Azure Data Factory, Spark, Databricks, and integration with Power BI and Copilot.
Strong understanding of Microsoft ecosystem and enthusiasm for Microsoft Fabric advancements.

Nice To Haves

Microsoft Fabric experience highly preferred.

Responsibilities

Architect, develop, and maintain modern data platforms, including data warehouses and lakes.
Design dimensional models that power reporting, analytics, and advanced insights.
Build and optimize ETL/ELT pipelines using advanced SQL and PySpark transformations.
Integrate data from diverse sources: SQL Server, Azure SQL, APIs, and flat files.
Collaborate on systems such as Dynamics 365 F&SCM and CE, AX, CRM, Infios WMS, custom microservices, and legacy applications.
Enable advanced analytics and AI/ML workloads through efficient, scalable data pipelines.
Champion consistency in naming conventions and calculations in partnership with data governance and business teams.
Implement robust data security measures, including access control, encryption, and auditing.
Participate in on-call support rotation for complex tier-2/3 incidents.
Stay ahead of industry trends, share knowledge, and proactively introduce innovative solutions.