Principal Data Owner - US Power Markets

Wood Mackenzie•Boston, MA

About The Position

Wood Mackenzie is investing in a unified data platform to support our analyst and commercial teams across Power, Gas, and Oil. As part of that investment, we are building out a dedicated data ownership function — a team of people who are unambiguously accountable for the quality, meaning, and fitness-for-purpose of our most critical data assets. The Principal Data Owner for Power Markets is the first hire into this function, and the work you step into is live and consequential. Our Power Market Intelligence team delivers daily fundamental and price forecasts across all seven North American ISOs, supporting more than 100 customer interactions every day with asset owners, traders, and energy retailers who make real market decisions in real time. The data you own is what reaches those analysts every morning. When it’s clean, normalized, and well-documented, they can focus on the work that matters. When it isn’t, everything downstream suffers. This is a hands-on, individual contributor role. The scope will grow as the function matures, and you will help shape what that growth looks like. You bring the domain expertise and the accountability. We provide the platform, the investment, and the cross-functional relationships to make the work stick. We’ll measure success by both internal and external impact. This is a role that sets the bar for what-good-looks-like for our internal teams and should be recognized by our customers as an SME on power market data too.

Requirements

Deep knowledge of North American Power markets — you should be able to look at a dataset from a US ISO and know immediately what it represents, how it is typically used, and what a data quality issue would look like.
Technical proficiency in SQL and Python at a working level — you do not need to be a data engineer, but you need to be able to understand what a data pipeline is doing and write or debug queries to investigate an issue.
A track record of owning data assets end to end — not just analysing data, but being accountable for its quality, provenance, and documentation in a production environment.
Experience working at the boundary between research or domain expertise and engineering — you are comfortable in both worlds and can hold your own in a technical conversation while also being the person analysts trust to understand the data they depend on.
A bias toward action and ownership. We need someone who finds ambiguity unacceptable and naturally moves to resolve it.
You are energized by building, not just operating. This is the first hire into a new capability. If the idea of helping establish processes, ways of working, and standards from the ground up appeals to you, this role was designed for someone like you.

Nice To Haves

Experience across multiple ISOs (e.g. ERCOT, CAISO, MISO, PJM, NYISO, ISO-NE, SPP) is strongly preferred.

Responsibilities

Being the single point of contact when data quality issues arise — analysts, engineers, and commercial teams should be able to reach you and get a definitive answer on what a dataset means, where it comes from, and whether something has gone wrong.
Owning the data quality bar for the Power lane of our data platform. You will define what “good enough” looks like at each stage of the data pipeline and hold that standard over time, iterating as our data and models improve.
Working closely with analytics engineering to validate that data transformations correctly reflect the business logic of Power market data, and documenting that logic in a way that can be shared and maintained.
Mapping and cataloguing the data assets you own — understanding what sources we ingest, what transformations are applied, and what downstream use cases depend on them.
Writing and maintaining data catalog documentation so that assets are well-described, discoverable, and useful to analysts and internal tooling.
Bridging the gap between engineering teams and research and analyst teams — translating between technical and domain language, and ensuring that when something breaks, ownership is clear and resolution is fast.
You will work across a globally distributed team that including a data operations team that runs overnight pipeline monitoring and hands clean data to the US analysts every morning. You speak both languages fluently. That means you can sit in a technical conversation with engineers and translate it into something analysts trust, and vice versa. When something breaks, ownership is clear and resolution is fast because you made sure it would be.