Data Engineer
We are looking for a Data Engineer to join our team in Salt Lake City, Utah and help build reliable, scalable data solutions that support key business initiatives. This role is ideal for someone who combines strong hands-on engineering ability with sound technical judgment and can guide decisions across architecture, delivery, and system improvement. The right candidate brings experience working with modern cloud services, data modeling practices, and collaborative development environments while communicating effectively with both technical and business partners.<br><br>Responsibilities:<br>• Lead the technical direction for a core data domain, making thoughtful architecture decisions that support scalability, reliability, and long-term maintainability.<br>• Design, build, and enhance data pipelines and platform components using Python, SQL, DBT, and cloud-based services within AWS environments.<br>• Develop data models aligned with Kimball methodology to support analytics, reporting, and downstream business use cases.<br>• Break large initiatives into clear technical workstreams, estimate effort, and drive execution against timelines while monitoring progress and addressing delivery risks.<br>• Work closely with cross-functional partners to convert business goals into practical data solutions and provide guidance on technical tradeoffs.<br>• Establish and reinforce engineering standards through code reviews, design discussions, and implementation of best practices for quality and performance.<br>• Identify areas of technical debt, prioritize remediation efforts, and balance platform stability with the delivery of new capabilities.<br>• Implement monitoring, alerting, and maintenance strategies that improve system health, data reliability, and operational visibility.<br>• Assess emerging tools and approaches to recommend improvements that strengthen system efficiency, searchability, and maintainability.
• 3+ years of experience in data engineering, software development, or a closely related technical field.<br>• Strong proficiency in Python and SQL, with experience building and optimizing production-grade data workflows.<br>• Hands-on experience with AWS technologies and cloud-native engineering patterns.<br>• Practical knowledge of DBT for data transformation, testing, and deployment.<br>• Familiarity with dimensional data modeling and Kimball methodology.<br>• Ability to lead technical discussions, influence architecture decisions, and communicate clearly across teams.<br>• Experience planning technical work, estimating effort, and managing competing priorities in a delivery-focused environment.
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- Salt Lake City, UT
- onsite
- Permanent / Full Time
-
90000 - 110000 USD / Yearly
- We are looking for a Data Engineer to join our team in Salt Lake City, Utah and help build reliable, scalable data solutions that support key business initiatives. This role is ideal for someone who combines strong hands-on engineering ability with sound technical judgment and can guide decisions across architecture, delivery, and system improvement. The right candidate brings experience working with modern cloud services, data modeling practices, and collaborative development environments while communicating effectively with both technical and business partners.<br><br>Responsibilities:<br>• Lead the technical direction for a core data domain, making thoughtful architecture decisions that support scalability, reliability, and long-term maintainability.<br>• Design, build, and enhance data pipelines and platform components using Python, SQL, DBT, and cloud-based services within AWS environments.<br>• Develop data models aligned with Kimball methodology to support analytics, reporting, and downstream business use cases.<br>• Break large initiatives into clear technical workstreams, estimate effort, and drive execution against timelines while monitoring progress and addressing delivery risks.<br>• Work closely with cross-functional partners to convert business goals into practical data solutions and provide guidance on technical tradeoffs.<br>• Establish and reinforce engineering standards through code reviews, design discussions, and implementation of best practices for quality and performance.<br>• Identify areas of technical debt, prioritize remediation efforts, and balance platform stability with the delivery of new capabilities.<br>• Implement monitoring, alerting, and maintenance strategies that improve system health, data reliability, and operational visibility.<br>• Assess emerging tools and approaches to recommend improvements that strengthen system efficiency, searchability, and maintainability.
- 2026-11-11T00:00:00Z