Wait, What Do You Do?

Overview

We are designing the grid of the future!

The Sr. Director, Enterprise Data Platform, Integration & Architecture will lead the strategy, buildout, and operation of EPE’s enterprise data ecosystem and related integration/platform services. This role will establish the modern data foundation needed to support trusted analytics, enterprise automation, approved AI use cases, and AI/ agentic systems.

Reporting to the CIO, this leader will translate enterprise priorities into a multi-year data, integration, governance, and AI-ready platform enablement roadmap. The role will partner across business and technology teams to ensure data is treated as a reliable internal product — secure, governed, scalable, observable, well-documented, and accessible through reusable patterns — aligned to measurable business outcomes.

This leader will build, lead, and coordinate a scalable global team and partner ecosystem across data engineering, data governance, integration, and platform services. This role will collaborate with business, engineering, software, and AI delivery teams to enable AI transformation by providing the governed data, system, and software-tool capabilities required for agentic workflows, while ensuring those capabilities are secure, reusable, observable, and sustainable.

Responsibilities

How you can make an impact:

Enterprise Data Platform & Architecture

Lead the design, implementation, and operation of EPE’s enterprise data platform, including modern data lake/lakehouse capabilities.
Define scalable data architecture patterns that support operational reporting, financial visibility, analytics, AI/ML, and GenAI use cases.
Establish curated data layers, canonical data models, and reusable data domains across the enterprise.
Ensure platform architecture aligns with enterprise standards for scalability, security, performance, and long-term maintainability.

Data Engineering & Integration

Build and govern reliable data pipelines, integration patterns, and data services across enterprise systems.
Partner with business applications, analytics, infrastructure, and security teams to ensure data flows are accurate, timely, and resilient.
Support the integration of enterprise platforms into EPE’s broader data architecture.
Partner with software and engineering teams to expose specialized engineering systems, modeling/simulation tools, and related data assets through secure, documented, versioned, and observable service interfaces for approved downstream consumers.
Manage the data and integration backlog, prioritizing work based on business value, risk, and strategic alignment.

Data Governance, Quality & Stewardship

Establish and mature EPE’s enterprise data governance framework.
Define standards for data quality, metadata, lineage, classification, access controls, and observability.
Partner with business leaders to define data ownership, stewardship responsibilities, and accountability across key data domains.
Lead governance forums that drive alignment, adoption, and trusted use of enterprise data.

Responsible Platform Enablement for AI Systems

Ensure EPE’s data ecosystem is prepared to support AI platforms, GenAI use cases, AI agents, and advanced analytics.
Partner with business, engineering, software, and AI delivery teams to enable prioritized AI opportunities by delivering the required data products, integration services, access patterns, and platform capabilities.
Establish responsible data access and AI practices, including governance for sensitive data, model inputs, and ethical use.
Ensure AI-related data capabilities are secure, scalable, and aligned with enterprise architecture and software development practices.

Platform Operations, Security & Reliability

Operate data and integration platforms with a focus on reliability, performance, monitoring, and incident response.
Provide visibility into platform health, delivery progress, risks, costs, and tradeoffs.
Ensure data platforms and services meet enterprise standards for access control, encryption, privacy, compliance, and security.
Partner with Cybersecurity, Legal, HR, and Compliance on incidents involving data misuse, breaches, or policy violations.

Leadership, Vendor & Business Partnership

Partner with executives and business leaders to align data initiatives with enterprise and departmental priorities.
Manage vendor relationships, platform/tooling decisions, contracts, and delivery outcomes.
Drive adoption, enablement, and training to help teams use enterprise data capabilities effectively.

Qualifications

Bring your passion, here's what’s needed:

Experience

Bachelor’s degree in Information Technology, Computer Science, Data, Engineering, or related field; master’s degree preferred.
15+ years of experience in data, technology platforms, enterprise applications, or IT leadership.
Proven experience leading enterprise data platform initiatives, such as Snowflake, lakehouse, or cloud data ecosystems; AWS experience preferred.
Experience building or leading data engineering, governance, integration, or platform teams.
Experience enabling AI-consuming systems — including GenAI, RAG, analytics, automation, and use cases spanning both IT-governed and software-team-owned applications — through governed data products, APIs, metadata, access controls, observability, and reusable integration patterns.
Experience designing secure access patterns for internal software teams and approved external technical partners, including least-privilege access, sandbox/prod separation, audit logging, credential management, and data-sharing controls.

Technical & Business Skills

Strong understanding of modern data platforms, data lake/lakehouse architecture, and cloud data ecosystems using both commercial off-the-shelf and open-source software.
Experience with data integration patterns, including ETL/ELT, APIs, streaming, and batch processing.
Knowledge of data governance, MDM, data quality, metadata, lineage, and data classification practices.
Demonstrated ability to design and govern contract-first integration patterns, including APIs, event streams, batch interfaces, semantic data products, schema/version management, testing, error handling, documentation, and service-level expectations.
Experience creating AI-ready data products with clear ownership, authoritative sourcing, semantic definitions, metadata, lineage, quality thresholds, sensitivity classification, permitted-use rules, and machine-readable documentation.
Experience establishing observability for data and integration services, including freshness, completeness, lineage, latency, failures, usage patterns, access anomalies, cost, and downstream impact.
Understanding of security, privacy, compliance, and access control requirements for enterprise data platforms.
Ability to translate business strategy into practical roadmaps, measurable outcomes, and delivery plans.
Ability to establish practical governance patterns that make approved data and system access faster, safer, and more reusable while mitigating risks.
Preferred: experience exposing specialized engineering, modeling, simulation, geospatial, scientific, or operational software through APIs, workflow services, data pipelines, or automation interfaces

Leadership & Operating Style

Strategic thinker with strong execution discipline.
Structured, accountable, and outcome-oriented.
Strong communicator with the ability to influence senior leaders and cross-functional stakeholders.
Comfortable operating in a growing and evolving environment with multiple in-flight initiatives that may need consolidation or cooperation.
Able to balance architecture, governance, delivery speed, risk, and business value.
Service-oriented platform leader who enables business, engineering, software, and AI delivery teams without unnecessarily centralizing control.
Comfortable enabling iterative pilots and production hardening in parallel, balancing near-term delivery needs with long-term platform standards.
Can build teams from existing resources and recruit necessary talent to meet objectives.

Why This Role Matters

EPE is scaling its technology and data capabilities to support continued growth, operational excellence, and AI-driven innovation. This role will be central to building the trusted enterprise data foundation that enables better decisions, improved automation, and agentic/AI-enabled ways of working.

Lead the Change!

Be a part of an innovative team shaping the grid of the future through advanced energy intelligence. For more than half a century, Electric Power Engineers (EPE) has partnered with power and energy clients across the globe, providing consulting expertise and energy intelligence software solutions for complex engineering and grid modeling challenges. As leaders in the renewables space, we are focused on building a modern, secure, and resilient grid. Join us in making an impact on the communities we serve and the environment in which we live. Together we can transform the future of energy.

How we support you:

Comprehensive health and wellness benefits including medical, dental, and vision with 100% premium coverage for you
Generous PTO and paid holidays
MyShare Employee Ownership Program
Work with industry leaders
401K, up to a 4% match (100% vested from day 1)

Location: This position will be located in Austin, TX

Travel: Occasional travel may be needed (10% or less)

EPE is an equal opportunity/AA/Disability/Veteran employer. The EEO is the Law poster, and its supplement are available using the following links: EEOC is the Law Poster

Third-Party Recruiting Notification

EPE does not accept unsolicited resumes from third-party recruiters. Any unsolicited third-party resumes forwarded by recruiters to EPE via our career page or to any of our managers or employees will be considered public information, may be treated as a direct application from the person identified in the resume, and will not be eligible for placement fee payment to the agency. EPE will not pay a fee to a third-party recruiter or agency without a previously signed third-party agreement and has not coordinated their recruiting activity with the appropriate member of the Talent Acquisition team.