Manager, Data and Applications Engineering

Xcel Energy•Minneapolis, MN

3d•$129,000 - $183,200

About The Position

Are you looking for an exciting job where you can put your skills and talents to work at a company you can feel proud to be a part of? Do you want a workplace that will challenge you and offer you opportunities to learn and grow? A position at Xcel Energy could be just what you’re looking for. Position Summary The Manager, Data & Applications Engineering leads the team responsible for building, owning, and sustaining the Xcel Vision Suite (XVS) applications and data ecosystem. XVS is Xcel Energy’s integrated planning platform that connects shared data, orchestration, and tools to enable coordinated planning across generation, transmission, distribution, and gas. In this role, the manager owns data ingestion and landing into Databricks for XVS- owned pipelines and ensures production-grade data services that are reliable, maintainable, and scalable. The manager sets engineering standards, manages delivery and consultant handoffs, and coordinates with Enterprise IT on platform patterns and requirements. The role oversees data engineers and data application engineers building Databricks -based pipelines and data applications (i.e. Databricks-native and Posit/Streamlit-style applications), including feature curation pipelines and Medallion (Bronze/Silver/Gold) architectures aligned with Data Science needs. The manager partners with Product and Data Science teams to productionize new capabilities and ensure XVS assets are sustainably supported.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Engineering, or related field is required.
At least 10 years of experience in one or more of the following areas: data engineering, software engineering, analytics engineering, or application development, including building production data pipelines and internal data applications on cloud platforms (e.g., Databricks on AWS).
Demonstrated success in a supervisory or lead role overseeing complex technical projects, vendor handoffs, and cross-functional delivery.
Strong relationship-building and partnership skills; ability to work effectively across multiple levels of the organization and with distributed teams (internal + consultants + Enterprise IT).
Strong written and verbal communication skills, including ability to synthesize technical tradeoffs and provide clear updates to leadership and stakeholders.
Strong problem-solving ability: both business and technical, with ability to diagnose issues and drive sustainable fixes.

Nice To Haves

Advanced degree in Computer Science, Engineering, Data Science, or related field.
Hands-on experience with Databricks (jobs/workflows, Delta tables, performance tuning, access controls) and modern data pipeline patterns.
Experience implementing Medallion architecture (Bronze/Silver/Gold), feature curation pipelines, and data quality validation patterns in Databricks.
Experience building and maintaining internal data applications (e.g., Python-based apps, dashboards, lightweight web apps) and integrating them with enterprise data platforms.
Comfort with ambiguity; able to translate conceptual needs into practical architecture and delivery plans.
Experience establishing engineering standards (repo patterns, CI/CD, testing, documentation, release practices) and improving operability of data/app systems over time.
Experience using AI‑enabled development tools and workflows (e.g., Claude Code, GitHub Copilot, or similar) to accelerate software and data engineering through assisted coding, code review, refactoring, and test generation, with appropriate human oversight and engineering standards.

Responsibilities

Own data engineering strategy and execution for XVS applications and pipelines not supported by Enterprise IT.
Establish and maintain standards for code quality, architecture patterns, testing, documentation, and deployment practices including data pipeline and service reliability practices, and a roadmap to reduce consultant dependency through reusable patterns, internal documentation, and repeatable delivery standards, to ensure long-term maintainability and consistent delivery across XVS tools.
Lead application and pipeline delivery, including executing data ingestion and landing into Databricks based on Data Science team requirements, and scaling solutions into durable XVS capabilities. Translate shaped scope into delivery plans; coordinate implementation across engineering staff and external vendors; ensure knowledge transfer and successful ownership transitions into the internal team. Ensure consultant-built pipelines include complete knowledge transfer to enable internal teams to operate and evolve them
Ensure operational reliability and supportability of XVS‑owned systems not supported by Enterprise IT. Oversee incident triage and resolution for XVS-owned apps/pipelines including production feature curation pipelines and Medallion-layer transformations (Bronze/Silver/Gold); implement monitoring/alerting, runbooks, and root-cause prevention; drive continuous improvement to reduce break/fix load.
Serve as the integration bridge across XVS delivery teams, Enterprise IT platform engineering, and Enterprise Data Engineering to synchronize delivery, standards, and data consistency across the company. Partner with Enterprise IT to apply platform patterns, security/compliance requirements, data integration standards, and environment constraints including alignment on ingestion patterns, data contracts, and Medallion-layer conventions where applicable; ensure consulting and internal builds adhere to these expectations while maintaining delivery velocity.
Perform management functions of the department including development of personnel. Lead, mentor, and develop data engineers and data applications engineers; manage capacity allocation across Product and Data Science requests; drive team health, performance, and delivery predictability.