Data Platform Lead

Fuse Energy

About The Position

Fuse is an AI-first energy company building an integrated energy business spanning renewable generation, hardware, grid infrastructure, real-time power trading, and distributed energy installations for consumers. The Data Platform Lead will own trading data end to end, from external data ingestion through to its use by traders and models. The role is accountable for data correctness, timeliness, reproducibility, and usefulness, and for delivering production-ready data quickly. The quality of this data directly affects the capabilities of Fuse’s trading desk. The role covers power market data, weather forecasts, grid and system data, fuel prices, and fundamentals. It includes delivering datasets and pipelines, maintaining data quality and monitoring, designing schemas that support point-in-time correctness and backtesting, managing data vendors, and leading a team of engineers. The role will also map data flows across the business to make it possible to onboard new sources while preventing downstream problems.

Requirements

Track record of owning and shipping data products to real users or customers, including pipelines, data quality, and delivery, with accountability for outcomes beyond implementation.
Track record of leading people and coordinating across teams, with a clear understanding of how data flows through a business.
Technical rigor and ability to profile systems and diagnose performance bottlenecks.
Strong schema-design skills for time-series and event data, including revisions, late-arriving data, and entity mapping across vendors.
Strong Python and SQL skills.
Experience running production pipelines at scale.
Experience evaluating and negotiating with data vendors, considering cost versus value.

Nice To Haves

Built or operated a data vendor business, or owned a comparable data product end to end.
Background in a trading firm, hedge fund, or other market-facing environment.

Responsibilities

Own trading data as a product, including power market data, weather forecasts, grid and system data, fuel prices, and fundamentals; ensure its reliability and usefulness to traders and quants.
Ship datasets and pipelines to production quickly and identify and resolve performance bottlenecks across ingestion, storage, and delivery.
Design canonical schemas supporting point-in-time correctness, revisions, and backtesting without lookahead bias.
Evaluate, onboard, and manage data vendors, assessing coverage, latency, licensing, and cost against trading value.
Build and operate monitoring for data freshness, completeness, and anomalies, with a clear process for responding to feed failures.
Lead and grow a team of engineers.
Map data flows across the business to enable rapid onboarding of new sources and prevent decisions that could cause downstream problems.