Kreate is a family-owned plastic injection molding company headquartered in Findlay, Ohio, with operations across five states. We create consumer goods sold by major retailers—products that improve everyday experiences for the people who use them.

What makes Kreate different is how we think. We’re on a mission to reimagine familiar product categories and turn “same old” into “new and improved.” That mindset drives everything we do—from product development and manufacturing to how we invest in our people and run our operations.

Innovation at Kreate isn’t limited to engineering or design teams. It shows up on the plant floor, in continuous improvement efforts, in how we adopt new technologies, and in how we support our teams. We’re always evolving—our processes, our tools, and our capabilities—because we believe the best ideas can come from anywhere.

As a family-owned company, we take a long-term approach to growth. We value accountability, collaboration, and people who take pride in their work. Here, you’ll have the opportunity to make an impact, learn new skills, and help shape how we build products and run our business.

If you’re looking for a place where innovation is expected, initiative is encouraged, and your work truly matters, we’d love to Kreate the future together.

We are seeking a Senior Data Engineer to transform our data into a scalable, reliable platform that supports analytics, applications, and machine learning. In this role, you will standardize development through GitHub and fully leverage Azure to maximize engineering velocity, improve data quality, and enable future AI and automation capabilities. You will bridge the gap between ML experimentation and production deployment, ensuring our data platform is robust, reliable, and ready for innovation. This is an opportunity to shape how data powers decision-making across the organization.

Key Responsibilities

• Deliver production-ready datasets and pipelines to support data science and analytics.
• Bridge the gap between ML experimentation and deployment with MLOps best practices.
• Build and deploy data-driven applications using Azure services.
• Maximize ROI on Azure investment through cloud-native architecture.
• Standardize development workflows using GitHub (version control, pull requests, CI/CD).
• Automate deployments and accelerate engineering velocity with GitHub Actions.
• Reduce bottlenecks for analysts, engineers, and data scientists by improving data accessibility and workflow efficiency.
• Enhance data quality, governance, and observability.
• Enable future capabilities such as AI, automation, and personalization.

Qualifications

• 5+ years of experience in data engineering or related roles.
• Proven experience in data engineering, cloud architecture, and MLOps.
• Strong proficiency in Python and SQL for data pipelines, automation, and data framework (Spark, Panda).
• Familiarity with REST APIs and application development concepts.
• Strong knowledge of Azure services (Data Factory, Synapse, Databricks, etc.) and cloud-native solutions.
• Proficiency with GitHub, including version control, CI/CD, and automation using GitHub Actions, workflows, and PR reviews.
• Experience delivering production-ready datasets and pipelines for analytics and ML.
• Ability to collaborate effectively with data scientists, analysts, and engineers to prepare and deliver clean, feature-ready datasets.
• Knowledge with data governance, observability, and quality best practices is preferred.
• Experience with real-time streaming tools (Kafka, Event Hub) also preferred.
• Strong problem-solving skills and a passion for building scalable, maintainable, and automated data platforms.
• Experience with Microsoft Fabric of Lakehouse architectures is a nice-to-have.

Company Details:

• Location: Remote
• This position will report to the VP of AI and Analytics

Kreate is an equal opportunity employer. The Statements used herein are intended to describe the general nature and level of the work being performed by an employee in this position and are not intended to be construed as an exhaustive list of responsibilities, duties and skills required. Furthermore, they do not establish a contract for employment and are subject to change at the discretion of the Company.