Position SummaryThis position designs, builds, and owns the technical capabilities that operationalize enterprise AI governance, spanning AI controls and risk assessments, implementation guidance, and working across Security, Architecture, Privacy, Legal, and Data Science teams. Working independently across multiple data domains, this role translates governance policy and regulatory requirements into enforceable technical controls, establishes the engineering patterns other team members follow, and serves as a technical resource to less experienced colleagues.
Essential Responsibilities- Data Quality Engineering: Design and implement data quality frameworks, rule sets, and scoring methodologies across multiple data domains, including measurement approaches for accuracy, completeness, timeliness, validity, consistency, and uniqueness. Define the remediation workflow and escalation model.
- Metadata and Catalog Engineering: Design and implement metadata and lineage capture automation spanning source systems, transformation layers, and consumption assets. Define harvesting strategy, integration approach, and the binding model between business glossary and physical assets.
- Data Classification and Protection Engineering: Develop classification and access control patterns, including attribute-based access control policies, tagging automation, and dynamic masking within the enterprise data platform. Partner with cyber security on control design and evidence.
- Solution Design and Technical Standards: Develop reusable governance components, libraries, and APIs, and establish the engineering patterns applied by other members of the team. Solve complex data management problems where existing approaches are insufficient, taking a new perspective on established solutions. Evaluate tooling and recommend platform capability, configuration, and integration approaches.
- Technical Leadership and Mentorship: Act as a technical resource and mentor to less experienced engineers. Review work products and provide guidance on standards, design, and troubleshooting. Lead technical workstreams within governance programs, including effort scoping, delivery sequencing, and progress reporting.
- Stakeholder Partnership: Partner with data owners, data stewards, platform engineering, enterprise architecture, and cyber security to translate governance policy into enforceable technical controls. Communicate technical design and trade-offs to non-technical stakeholders.
Minimum Requirements- Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field, or an equivalent combination of education and experience.
- Five or more years of experience in data management, data engineering, or data governance engineering.
- Advanced SQL proficiency and demonstrated proficiency in Python.
- Demonstrated experience implementing at least one enterprise data management capability end to end, such as data quality, metadata and catalog, master data, or data access control.
- Demonstrated ability to design technical solutions independently and defend design decisions to technical and business stakeholders, including experience working across multiple data domains or business functions.
Preferred Qualifications- Experience implementing controls in a SOX, NERC CIP, or privacy-regulated environment. Gas and/or Electric Utility Industry experience preferred.
- Certifications such as IAPP AIGP (AI Governance Professional), CIPP/CIPM, CDMP (data management), or CISA/CRISC.
- 5-7 years or more in data governance, AI/ML risk, model risk management, IT compliance or audit.
- At least 2 years working directly with AI/ML or generative AI systems, such as model reviews, use-case intake or risk assessments.
- Experience in a regulated industry like utilities, energy. Familiarity with NERC CIP, FERC or state public utility commission oversight is especially valuable.
- Hands-on use of the NIST AI Risk Management Framework (AI RMF), ISO/IEC 42001 and 23894, and model risk guidance such as SR 11-7.
- Working knowledge of the EU AI Act, U.S. state AI laws (for example, Colorado), and privacy rules like CCPA and GDPR.
- Understanding of responsible AI principles: fairness, transparency, explainability, accountability, privacy and safety.
Non-Bargaining
The anticipated starting base pay for this position is: $97,600.00 to $159,100.00 per year
This position is eligible for the following benefits: Annual Incentive Program, Medical/Pharmacy Plan, Dental, Vision, Life Insurance, Dependent Care Flexible Spending Account, Health Care Flexible Spending Account, Health Savings Account (HSA) (if enrolled in eligible health plan), Limited-Purpose FSA (if enrolled in eligible health plan and HSA), Transportation Reimbursement Account, Short-term disability (STD), Long-term disability (LTD), Employee Assistance Program (EAP), Fitness Center Reimbursement (if enrolled in eligible health plan), Tuition reimbursement, Transit programs, Employee recognition program, Pension, 401(k) plan, Paid time off (PTO), Holidays, Volunteer Paid Time Off (VPTO), Parental Leave
Benefit plans are subject to change and Xcel Energy has the right to end, suspend, or amend any of its plans, at any time, in whole or in part.
In any materials you submit, you may redact or remove age-identifying information including but not limited to dates of school attendance and graduation. You will not be penalized for redacting or removing this information.
Deadline to Apply: 11/24/26
All Xcel Energy employees and contractors share responsibility for protecting the company's information and systems by adhering to cybersecurity policies, standards, and best practices, recognizing that cybersecurity is everyone's responsibility.
