Data Engineer

Xcel Energy•Denver, CO

1d•Hybrid

About The Position

The Data Engineer is a hands-on engineer on Xcel Vision Suite (XVS) Data & Applications Engineering team and reports to the Manager of Data & Applications Engineering. The role builds and evolves data pipelines, internal applications, dashboards, and engineering workflows supporting XVS across generation, transmission, distribution, and gas planning. It works closely with Product, Data Science, Enterprise IT, and external consultants to turn planning workflows, data science outputs, and consultant-delivered solutions into maintainable internal capabilities. The Data Engineer helps establish and follow standards for code quality, testing, documentation, deployment, and knowledge transfer, and contributes to a practical, scalable approach for building, shipping, and maintaining XVS tools. The position requires sound technical judgment, comfort with ambiguity, and the ability to translate loosely defined needs into usable tools and data products for planners and engineers. It also applies automation and AI-assisted development practices to improve delivery speed, consistency, and quality.

Requirements

Seven years of related functional experience.
Bachelor's degree in Technology, Science, Business, or a related field, or four years of experience equivalent to the position.
Excellent communication skills, including the ability to communicate with varying organizational levels and skill sets and translate between technical and non-technical concepts.
Excellent relationship management and collaboration skills, with a record of working across organizations to drive innovation and business results.
Experience managing the lifecycle of technical solutions.
Deep subject matter expertise in relevant system domain products, platforms, processes, and architecture.
Broad general knowledge of technology architecture, infrastructure, networks, security, and software principles and models.
Experience partnering with internal and external vendors.
Proven analytical, problem-solving, and troubleshooting skills.
Extensive knowledge of future technology trends within the area of expertise.
Demonstrated technical leadership on large-scale projects.
Experience with delivery methodologies such as Waterfall, Agile, and Scrum, and operational models such as ITIL.
Experience and understanding of core IT Service Management functions, such as Change Management and Incident Management.

Nice To Haves

Hands-on experience with Databricks, including jobs and workflows, Delta tables, performance tuning, Unity Catalog, and access controls.
Experience implementing Medallion architecture (Bronze/Silver/Gold), feature pipelines, and data quality frameworks.
Experience building and maintaining internal data applications, such as Databricks apps, Lakebase, and dashboards, integrated with enterprise platforms.
Ability to translate ambiguous business needs into well-designed, maintainable data solutions.
Experience with engineering standards, including repository structures, CI/CD, testing frameworks, documentation, and release practices.
Experience supporting data-system operability and reliability, including monitoring, alerting, and troubleshooting.
Experience using AI-enabled development tools such as Genie Code, Claude Code, or similar tools to enhance engineering productivity.
Experience in federated or self-service data environments and enabling domain teams to publish and consume data products.
Experience developing production-quality applications and services using Python, APIs, and modern software engineering practices, with an emphasis on maintainable, reusable data solutions.

Responsibilities

Lead and support technical activities throughout the solution lifecycle.
Ensure solutions are designed for a strong user experience and operational performance.
Lead solution design, continuously integrating Enterprise Architecture, Security, Operations, and Compliance considerations.
Provide input to cost and schedule estimates.
Maintain responsibility for the overall integrity of system design and operation.
Oversee vendor activities.
Review solution performance and continually assess system health.
Track and raise awareness of operational and technical debt risks.
Provide escalated support for incident and problem management.
Use analytics to improve availability, reliability, efficiency, and capacity.
Stay current with and apply technical industry knowledge in the relevant domain.
Conduct peer reviews and approve system changes and technical solution designs.
Coach and mentor less experienced team members.
Partner across organizations to drive minimal costs for optimal solutions.
Provide in-depth technical information to stakeholders as needed.