Listing evidence and provenance
- Source
- Workday View original listing
- Freshness
- Open in the current public read path; this is not an employer guarantee.Last observed October 5, 2026
- Classification
- Modern power-system classification not yet published for this listing.Legacy source industry field: Grid Infrastructure
- Pay provenance
- Employer-provided pay
Job Description
Leads ERCOT’s Data Products and AI Strategy organization, driving enterprise data product development, analytics and business intelligence solutions, and AI capabilities that enable ERCOT’s vision to be the most reliable and innovative grid in the world.
Key Responsibilities
- Responsible for hiring, coaching, training, and performance management of staff.
- Regularly interacts with executives and/or major customers. Interactions frequently involve special skills, such as negotiating with customers or management regarding matters of significance to the organization.
- Typically directs and controls the activities of a broad functional area through several department managers within ERCOT. Has overall control of planning, staffing, budgeting, managing expense priorities, and recommending and implementing changes to methods.
- Responsible for budgetary decisions within functional areas according to organizational policy/guidelines. Recommends financial decisions that impact area of responsibility.
- Define and execute enterprise data product and AI strategy aligned with organizational objectives and innovation initiatives.
- Develop multi-year roadmaps for data product innovation, analytics capabilities, and AI/ML maturity.
- Drive digital transformation through advanced analytics, data products, and artificial intelligence.
- Own enterprise data product portfolio planning, prioritization, and lifecycle management.
- Ensure predictable, high-quality delivery of data products, analytics assets, and ML models.
- Define enterprise standards for data product specifications, validation frameworks, and MLOps practices.
- Embed governance, risk, and compliance controls across data products and AI/ML models.
- Ensure ethical AI practices, fairness assessments, and responsible AI frameworks are integrated into operations.
- Drive privacy-by-design and security-by-design principles across all data products and AI initiatives.
- Build and lead high-performing teams across data product management, analytics, and AI/ML operations.
- Establish organizational structure, roles, and career development frameworks to support strategic goals.
- Develop and manage annual budgets, expense priorities, and ROI tracking for strategic investments.
- Collaborate cross-functionally with IT, business domains, regulatory affairs, and technology partners.
- Build trusted advisor relationships with executives and facilitate governance forums for data and AI initiatives.
- Negotiate with internal and external stakeholders on product requirements, SLAs, and delivery commitments.
- Manage escalations, resolve conflicts, and maintain transparency with executive leadership.
- Sponsor innovation programs, pilot projects, and adoption of industry best practices for analytics and AI.
- Benchmark capabilities against industry peers and foster a culture of continuous improvement.
- Coordinate unified strategies and priorities with platform and governance teams to ensure alignment.
- Represent the organization in industry forums, conferences, and strategic partnerships related to data and AI.
Requirements
- Experience
- Requires minimum 10 years job related work experience and 5 years in a management or leadership role in excess of degree requirements. Minimum years of job related experience can include time in leadership roles.
- Requires minimum of 10 years of progressively responsible experience in data products, analytics, business intelligence, AI/ML or generative AI domains
- Demonstrated experience building and scaling data products, analytics organizations and AI application development teams
- Proven track record developing and deploying AI-powered applications, including LLM-based systems, agentic AI, RAG architectures, or autonomous agents in production environments
- Exceptional people leadership with ability to build, develop, and retain high-performing technical teams
- Deep understanding of data product management, analytics development, MLOps practices and AI product life cycle development.
- Strong knowledge of modern data platforms, cloud architecture, analytics technologies, and generative AI infrastructure.
- Experience with AI governance frameworks, responsible AI practices, model evaluation, and safety/alignment considerations for production AI systems
- Education
- Bachelor's Degree: Electrical Engineering, Computer Science or related field (Required)
- Master's Degree: MBA, Data Science, Computer Science, Engineering or related field (Preferred)
- or a combination of education and experience that provides equivalent knowledge to a major in such fields is required
Ready to Apply?
Apply directly on ERCOT's site
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