Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Pattern Energy via LinkedIn
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.
Responsibilities
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 growt