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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Management Engineer - **Company:** Xcel Energy Inc. - **Location:** Denver, CO, United States - **Experience:** Expert - **Salary:** $97,600.0 - $138,600.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Cyber Security, Information Systems, Information Engineering, Data Governance, Data Security, Python (Programming Language), Metadata, Reference Data, Enterprise Data Management, Data Classification, Sql Optimization, Information Technology, Data Analytics, Data Management, Databricks - **Published:** September 10, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=54b8fd4a77a55734 ## About the Role * 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 Requirements * Experience implementing and standing up DQX on Databricks (Data Quality Framework). * Six to eight years of relevant experience. * Hands-on experience with Databricks and Unity Catalog, including attribute-based access control and tag-based policy. * Data modeling experience across conceptual, logical, and physical layers. * Experience implementing controls in a SOX, NERC CIP, or privacy-regulated environment. Gas and/or Electric Utility Industry experience preferred. * Data certification preferred (CDMP) upon hire or to acquire within first year of employment. ## Description This position designs, builds, and owns the technical capabilities that operationalize enterprise data governance, spanning data quality, metadata and catalog, classification and data protection, and master and reference data. 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., * 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. 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