Senior Director, Enterprise Data Architecture and Analytics

Company Overview
Pattern Energy is a leading renewable energy company that develops, constructs, owns, and operates high-quality wind and solar generation, transmission, green fuels and energy storage facilities. Our mission is to transition the world to renewable energy through the sustainable development and responsible operation of facilities with respect for the environment, communities, and cultures where we have a presence. 

Our approach begins and ends with establishing trust, accountability, and transparency. Our company values of creative spirit, pride of ownership, follow-through, and a team-first attitude drive us to pursue our mission every day. Our culture supports our values by fostering innovative and critical thinking and a deep belief in living up to our promises. 

Headquartered in San Francisco, Pattern has a portfolio of 30 power facilities and transmission assets across North America, serving various customers that provide low-cost clean energy to millions of consumers. 

Job Purpose
The Senior Director of Enterprise Data Architecture & Analytics serves as the executive leader of Pattern Energy’s enterprise-wide data and analytics function. This role sets the long-term vision, strategy, operating model, and investment roadmap for Pattern’s data ecosystem across platforms, governance, architecture, product management, and delivery.

As the enterprise authority on data strategy, this leader ensures the organization is equipped with a scalable, governed, AI-ready data foundation aligned to Pattern’s business priorities, operational realities, and future growth. The Senior Director drives cross-company alignment, influences enterprise decision-making, and ensures the team delivers measurable business impact across all domains, including Operations, Finance, Trading, Development, Asset Management, and Corporate, and Market Fundamentals.

This role leads a multi-disciplinary organization of Product Managers, Delivery Teams, Solution Architects, Platform Leads, and Governance experts while also managing strategic vendor relationships, executive stakeholders, and enterprise data investments.

Key Accountabilities 

Strategic Leadership & Vision

• Define and execute the enterprise data and analytics strategy, ensuring alignment with business priorities and long-term technology roadmaps.
• Establish a unified operating model including product management, agile delivery, architecture, and governance.
• Drive architectural modernization, federation of analytics, and AI-enablement across the company.

Enterprise Data Architecture Oversight

• Lead enterprise architecture across data engineering, BI, AI/ML, data governance, cloud, and integrations.
• Ensure scalable, domain-aligned architectures using Databricks Lakehouse, ADLS, Delta, Medallion patterns, Purview, and Azure cloud services.
• Govern standards for data modeling, data quality, metadata, lineage, MDM, and integration patterns.
• Alignment with enterprise applications architecture and tooling used across business domains.

Product Delivery & Portfolio Leadership

• Oversee the Product Manager, Product Solutions Architects, and Technical Delivery Manager to deliver high-quality, high-velocity outcomes.
• Maintain and prioritize product portfolio across enterprise data engineering, analytics, AI, and governance initiatives.
• Drive repeatable delivery, best-practice DevOps, and consistent platform enablement.

Platform Ownership & Technical Stewardship

• Own enterprise data platform strategy: Databricks, ADLS, Purview, Azure DevOps, enterprise semantic layer, and BI, AI, and Analytics tools.
• Set standards for scalability, performance, cost optimization, and operational excellence.
• Lead adoption of emerging technologies, including generative AI, self-service data, and embedded analytics.

Operational Service Delivery & Support

• Oversee day-to-day operational support for the enterprise data and analytics ecosystem for business-critical workflows and 24-7 support.
• Ensure SLAs, incident response, change management, and environment reliability across data pipelines, models, BI content, and platform services.
• Partner with Managed Service Providers and internal teams to ensure high system uptime and timely issue resolution.
• Establish monitoring, alerting, and operational dashboards to ensure proactive maintenance and reduce downtime.
• Drive continual improvement in system performance, user satisfaction, and operational efficiency. 

Governance & Risk Management

• Oversee enterprise data governance, data quality, security, privacy, retention, and compliance frameworks.
• Ensure governance is scalable and federated, enabling the business without slowing delivery.
• Reduce technical debt and enforce best practices across the enterprise.

Leadership, Coaching & Cross-Functional Alignment

• Lead a team of employees and contractors across Platform, Intelligence, Governance, Product, and Delivery. Ensures the team growth both technically and on execution and leadership skills
• Partner closely with business leaders and federated data/analytics teams across the enterprise, ensuring prioritization, communication, and goal planning is aligned to accelerate and deliver business outcomes.
• Build a culture of transparency, accountability, collaboration, and continuous improvement.
• Manage third party relationships, negotiate contracts, and identify opportunities to grow and support the team with necessary resources.
• Budget, Purchase Order, and Invoice management to meet team goals within scope of allocated funds.

Education/Experience/Qualifications Required

Educational Experience

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Analytics, or related field required.
• Master’s degree in Information Systems, Data Science/Analytics, or MBA preferred.
• Equivalent experience may be considered.

Work Experience

• 12-15+ years of progressive experience in Data Architecture, Enterprise Data Engineering, BI/Analytics, or related fields.
• 8+ years leading data/analytics teams, including architects, engineers, BI developers, product managers, or delivery teams.
• Proven experience operating a modern data ecosystem using cloud Databricks Lakehouse technologies.
• Experience implementing governance frameworks, semantic layers, metadata management, and federated analytics models.
• Demonstrated success delivering large, complex, business-critical data solutions end-to-end.
• Experience leading agile product teams and managing an enterprise project/product portfolio.
• Strong understanding of AI capabilities and technologies
• Experience managing budgets, vendor relationships, RFPs, and large delivery organizations.

Qualifications

• Executive level leadership presence with the ability to influence VP and SVP-level stakeholders.
• Ability to translate business needs into scalable product roadmaps, architectures, and delivery frameworks.
• Expertise leading teams in a hybrid model of FTEs and outsourced/contract engineering partners.
• Deep understanding of Azure cloud, data engineering best practices, warehousing/lakehouse architecture, MDM, and metadata governance.
• Ability to drive organizational change, modernize legacy systems, and introduce scalable frameworks.
• Strong communication and storytelling ability, capable of simplifying complex technical concepts for non-technical audiences.
• Demonstrated success building relationships with cross-functional business partners.
• Strong problem solver with an ability to anticipate risks, remove roadblocks, and ensure business continuity.

Technical Skills

• Platforms & Cloud:
  • Databricks Lakehouse, Azure Data Lake Storage Gen2, Azure Synapse, Azure ML, Azure Functions, Azure DevOps
• Data Engineering & Architecture:
  • Delta Lake, Medallion architecture, ETL/ELT, CI/CD, pipeline orchestration, streaming, DevOps
• Governance & Security:
  • Microsoft Purview (data catalog, lineage, classifications, DQ rules), RBAC/ABAC, metadata management, domain-based governance models
• BI, AI & Analytics Tools:
  • Power BI or similar BI tools, semantic modeling, AI/ML pipelines, enterprise analytics architectures
• Programming & Modeling:
  • SQL, Python preferred; familiarity with dbt is a plus
• Operating Model Tools:
  • Product road mapping, agile delivery frameworks, Jira/Azure DevOps Boards, portfolio management

The expected starting pay range for this role is $174,000 - $216,000 USD. This range is an estimate and base pay may be above or below the ranges based on several factors including but not limited to location, work experience, certifications, and education. In addition to base pay, Pattern’s compensation program includes a bonus structure for full-time employees of all levels. We also provide a comprehensive benefits package which includes medical, dental, vision, short and long-term disability, life insurance, voluntary benefits, family care benefits, employee assistance program, paid time off and bonding leave, paid holidays, 401(k)/RRSP retirement savings plan with employer contribution, and employee referral bonuses.

Pattern Energy Group is an Equal Opportunity Employer.

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