Principal Data Architect - Battery Storage

Principal Data Architect - Battery Storage

Remote

Plus Power is an energy storage market leader, with a market-leading 10+ GW portfolio across more than 25 states that will transform North American electric grids into cleaner and more versatile critical infrastructure.

Standalone energy storage is rapidly transforming the North American energy markets, because it is cheaper than new natural gas plants, faster to build than fossil peakers or transmission, and able to perform diverse energy services. Plus Power partners with electricity system operators, utilities, and investors to originate, develop, finance, own and operate standalone energy storage projects that provide critical services to the wholesale electric market.

Plus Power’s team applies an intentional mindset to energy storage development by using a data‑driven approach to development and operations.

At Plus Power, we are focused on solving hard climate problems, profitably. We are growing fast, and value candidates who, like us, share a focus on setting high expectations, owning and learning from mistakes in the spirit of radical transparency, and are committed to internal partnering as a key element of our ideas meritocracy. Our team praises Plus Power’s culture and excels through our game‑changing mission and supportive ecosystem.

Plus Power recruits outstanding energy industry professionals who are driven to develop, build and operate assets safely and reliably to decarbonize the power markets while growing their careers. Our team looks for data-driven and fact-based mindsets, engaging and collaborative behaviors, and personal growth-focused professionals.

We are looking for a Principal Data Architect to help us turn a fast‑growing, multi‑source data environment into a coherent, trusted, and easy‑to‑use analytical ecosystem. You’ll set the strategic north star for how we define, organize, and use data across the company, then drive pragmatic, incremental steps to get us there. This is a highly collaborative role: you’ll bring together analysts, engineers, and business stakeholders to establish working standards that are clear, realistic, and adopted in practice.

We value directness, meaningful relationships, and transparency: surfacing disagreements early, grounding decisions in facts, and aligning people around shared outcomes even when incentives and perspectives differ. This role sits at the intersection of data architecture, analytics platforms, and data engineering, with a strong emphasis on data modeling, shared definitions, and scalable analytical systems.

A major focus will be evangelizing and operationalizing our data catalog and shared definitions: partnering with stakeholders to name and normalize data assets, build an expressive model of our institutional knowledge, and create a “common language” that scales across many teams and analyst skill levels. You’ll work closely with our Data and Cloud Engineering team on ELT patterns, schema evolution, and durable conventions.

You will balance long‑term consistency with rapid learning and iterative delivery. This isn’t an “ivory tower” architecture role, you’ll stay close to the work, prototyping and writing code where it accelerates progress, and building lightweight processes and tooling that make the right way the easy way. Success looks like continuous delivery of visible value: better discoverability, fewer conflicting metrics, and steadily increasing trust while we converge, step by step, on a clear long‑term architecture.

• Define and evolve data architecture standards for analytics and reporting, including data modeling, naming conventions, schema design, and documentation practices across the organization
• Own the data catalog and metadata strategy, partnering with stakeholders to define, name, and organize data assets across multiple domains and source systems
• Collaborate closely with Principal Data Engineering leadership and application engineering teams to align on ELT patterns, Snowflake usage, schema evolution, and analytical data modeling practices
• Contribute hands‑on through SQL and Python, developing reference data…