IT Director

Manager Information Technology (M3) - Data Foundations Puget Sound Energy is looking to grow our community with top talented individuals like you! With our rapidly growing, award winning energy efficiency programs, our pathway to an exciting and innovative future is now. PSE's Data & AI team is looking for qualified candidates to fill an open Manager Information Technology (M3) - Data Foundations position! Specific details regarding the work arrangements for this position will be discussed in further detail during the interview process. Job Description The Manager, Enterprise Data Foundations leads managers and senior technical professionals across data engineering, data platform, data architecture, data governance, data quality, and data operations. This position is accountable for the end-to-end data foundationfrom source ingestion and orchestration through governed, production-ready data products and services. The position owns the strategy, operating model, roadmap, and operational performance of PSE's enterprise data foundation capabilities, including the Unified Data Platform, lakehouse and data warehouse services, data integration and orchestration, APIs, metadata and lineage, data quality and observability, data lifecycle management, and secure data access. This leader works across business, IT, and operational technology organizations to ensure that trusted data supports operational decision-making, regulatory reporting, analytics, artificial intelligence, customer outcomes, and grid reliability. Success will be measured through platform reliability, faster data onboarding, improved quality and lineage, increased reuse of governed data products, reduced duplication and technical debt, and measurable business value. Job Responsibilities Has overall direction and accountability for PSE's enterprise Data Foundations capabilities, including data engineering, data platform, data architecture, data governance, metadata and lineage, data quality and observability, data integration and orchestration, API enablement, and data lifecycle management. Owns and executes the multi-year Data Foundations strategy, roadmap, operating model, and investment plan in alignment with PSE's Data & AI strategy, enterprise architecture, and business priorities. Directs teams through subordinate managers and senior individual contributors. Establishes clear accountabilities, operating rhythms, development plans, performance expectations, and succession plans. Responsible for the end-to-end design, development, delivery, maintenance, reliability, security, performance, capacity, and cost management of PSE's Unified Data Platform and supporting hybrid-cloud data services. Establishes and enforces enterprise architecture patterns, engineering standards, data contracts, naming conventions, reusable components, quality thresholds, and security controls for data ingestion, storage, transformation, access, sharing, archival, and retirement. Leads enterprise data ingestion and orchestration capabilities supporting batch, micro-batch, near-real-time, and streaming data. Establishes governed API and event-driven patterns for data access and integration. Leads enterprise data governance and catalog capabilities, including data ownership and stewardship, metadata, lineage, classification, critical data elements, data quality, access controls, retention, and approved internal and external data sharing. Partners with Information Security, Privacy, Records, Risk, Compliance, Enterprise Architecture, IT Operations, Applications, Integration, and business and operational technology teams to embed controls throughout the data lifecycle. Ensures that high-value data is published as trusted, discoverable, reusable, and AI-ready data products with identified owners, documented definitions, clear service expectations, and consistent enterprise metrics. Partners with analytics, AI, application, integration, and business teams to prioritize foundational work based on business value, operational risk, regulatory requirements, enterprise reuse, and strategic alignment. Drives modernization and simplification of PSE's data estate, including migration and retirement of legacy data warehouses, data marts, point-to-point integrations, redundant pipelines, shadow data stores, and duplicative reporting assets. Establishes DataOps and DevSecOps practices, including version control, continuous integration and deployment, automated testing, environment management, infrastructure automation, security validation, and controlled release processes. Additional Responsibilities Establishes operational support practices for enterprise data services, including monitoring and observability, incident and problem management, change management, service recovery, root-cause analysis, and continuous improvement. Establishes service levels, service objectives, and key performance indicators for platform availability, pipeline reliability, data freshness, data quality, catalog and lineage coverage, data onboarding cycle time, product reuse, adoption, capacity, and cost. Develops and maintains disaster recovery and business continuity capabilities for enterprise data platforms, pipelines, catalogs, APIs, and supporting services. Builds and maintains trusted relationships with senior leaders, business stakeholders, enterprise architects, application owners, operational technology teams, vendors, and implementation partners. Owns resource planning, annual and multi-year budgets, platform capacity, software licensing, vendor performance, contracts, consulting relationships, service levels, and delivery commitments for the Data Foundations function. Evaluates emerging technologies and industry practices and determines where they can improve platform reliability, governance, productivity, scalability, security, cost efficiency, or business outcomes. Communicates strategy, roadmaps, delivery status, service performance, risks, decisions, and investment requirements to senior leadership and other enterprise stakeholders. Keeps pace with current technologies, architecture patterns, utility data practices, regulatory expectations, and relevant industry standards. Performs other duties as assigned. Minimum Qualifications Bachelor's degree in computer science, engineering or related discipline; or equivalent combination of education and work experience. Proven knowledge of information technologies and methodologies related to assigned IT segment or area. 10 years experience managing or leading teams (some could include consulting) in strategic planning, development, implementation, and maintenance of IT system, application, infrastructure service or other technology areas. 5 years experience managing Enterprise Data Warehouse and Business Intelligence environments, including experience with database design, data modeler, administration and optimization. Background in large data warehouse environments, including Extract, Transform & Load (ETL) and parallel, mixed-mode processing in the data warehouse. Experience with data governance and processes. Deep background in metadata management and metadata management tools, multi-tier reporting systems design and support practices, including architecture, engineering, configuration, tuning, and capacity planning. Experience in developing data conversions, interfaces, complex reports/extracts, and workflow. Ability to blend creativity, problem-solving, and technical skills for refining existing theories or developing new system approaches to seize opportunities to sustain business success. Ability to influence without authority, gain consensus and drive organizational adoption. Deep understanding of project and software development ASAP or Agile methodologies and can demonstrate proficiency in the applied use of systems and process analysis tools. Full system life cycle experience, including development lifecycle methodologies. Proven problem solving, organizational, analytical and decision making abilities based on sound business judgment and the application of impact analysis. Demonstrates: Strategic thinking and leadership with strong abilities in relationship management. Competency in project management discipline and the execution of multiple and/or large projects. Leadership with multidisciplinary, high-performance work teams/groups. Successful development and implementation of new technologies. Competency in business processes, and process improvements. Competency in developing efficient and effective solutions to diverse and complex business problems. Demonstrated management and decision making skills concerning information systems policies, processes and procedures with proven track record of completing tasks and/or project in on budget and on schedule. Excellent communication and presentation skills, especially with non-technical managers. Solid oral and written communications skills. An ability to present and discuss technical information in a way that establishes rapport, persuades others, and gains understanding. Exceptional analytical, problem-solving and conceptual skills that can be applied to multiple domains and enterprise-wide. Exceptional negotiating and critical thinking skills. Customer-oriented, a positive, team-oriented attitude, flexibility, an understanding of business issues driven by the need for information technology, and solid work ethic are expected. Desired Qualifications Master's degree in computer science, data or information systems, engineering, business administration, or a related discipline. Experience leading organizations through subordinate managers and senior technical leaders across data engineering, platform engineering, data architecture, governance, quality, and operations. Experience defining and executing an enterprise data strategy and multi-year technology roadmap within a large, complex, or regulated organization. Experience implementing and operating enterprise-scale lakehouse, data warehouse, and data platform capabilities in hybrid-cloud environments. Experience with Microsoft Fabric and OneLake, Microsoft Purview, Power BI, Azure data services, AWS data services, SAP S/4 HANA, or comparable enterprise technologies. Strong knowledge of modern data architecture patterns, including lakehouse architecture, dimensional and domain-oriented modeling, ETL and ELT, batch and streaming processing, event-driven integration, APIs, data contracts, semantic models, and reusable data products. Experience establishing an enterprise data governance operating model encompassing data ownership and stewardship, metadata, lineage, classification, critical data elements, master and reference data, data quality, lifecycle management, and role-based access. Experience partnering with cybersecurity, privacy, records, legal, risk, and compliance organizations to implement data classification, Data Loss Prevention, retention, auditability, and secure data-sharing controls. Experience establishing DataOps, DevSecOps, continuous integration and deployment, automated data testing, observability, site-reliability practices, service management, and disaster-recovery capabilities. Proven experience modernizing or decommissioning legacy data warehouses, data marts, ETL platforms, reporting environments, point-to-point integration, and duplicative data solutions. Experience creating and operating product-oriented data services with roadmap, service-level objectives, ownership, adoption measures, lifecycle plans, and demonstrated value realization. Experience leading enterprise platform budgets, capacity and licensing plans, vendor relationships, contracts, consultants, and strategic implementation partners. Understanding of the operational, security, regulatory reliability and data governance considerations associated with integrating IT and operational technology data. Relevant certifications such as Certified Data #J-18808-Ljbffr