Fuse Energy supplies electricity to individuals and develops its own renewable generation facilities.
Data Platform Lead
Fuse Energy is hiring a Data Platform Lead to manage trading data end to end, from external sources through to traders and models. The role covers designing and deploying pipelines, data quality and managing a team of engineers, using Python and SQL. Experience in trading or market environments is an advantage, with a competitive salary, equity and a biannual bonus.
Information about Fuse Energy
- Official domain
- fuseenergy.com
- Open jobs
- 62
Job details
The full description published by Fuse Energy.
Description de l’offre
Fuse is an AI-first energy company on a mission to make energy abundant and affordable, fast. We combine first-principles thinking with cutting-edge technology to build a radically better energy system. We've raised over $200M from top-tier investors including Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, 20VC, Hummingbird and Collaborative Fund, alongside strategic angels including Nico Rosberg and GPs behind Meta, Revolut, Spotify and Uber.
We're building a fully integrated energy company: developing our own solar, batteries and other generation projects, building our own hardware, improving and developing grid infrastructure, trading power in real time, and installing distributed energy in homes. By selling directly to consumers, we cut out the middleman, lower costs and pass the savings on to our customers. We’re hiring a Data
Lead to own trading data end to end, from the moment external data enters Fuse to the moment a trader or model relies on it. You’ll be accountable for whether that data is correct, timely, reproducible and actually useful, and you’ll get it into production fast. Every model and trading decision we make depends on it, so this role sets the ceiling on what the desk can do.
Responsibilities
Own trading data as a product, covering power market data, weather forecasts, grid and system data, fuel prices and fundamentals, and be accountable for its reliability and usefulness to traders and quants.
- Ship datasets and pipelines to production quickly and find and fix performance bottlenecks across ingestion, storage and delivery.
- Design canonical schemas that support point-in-time correctness, revisions and backtesting without lookahead bias, applying rigour where it pays off and moving fast where it doesn’t.
- Evaluate, onboard and manage data vendors, including coverage, latency, licensing and cost against trading value.
- Build and run monitoring for freshness, completeness and anomalies with a clear process when a feed breaks.
- Lead and grow a team of engineers and map how data flows across the business so you can plug in new sources quickly and block decisions that would cause problems downstream.
- Track record of owning and shipping data products to real users or customers, including the pipelines, data quality and delivery, and being accountable for outcomes rather than only the implementation.
- Track record of leading people and coordinating across teams with a clear understanding of how data flows through a business.
- Technical rigour: you can go deep, profile a system and untangle performance bottlenecks.
- Strong schema design for time series and event data, including revisions, late-arriving data and entity mapping across vendors.
- Strong Python and SQL and experience running production pipelines at scale.
- Experience evaluating and negotiating with data vendors with a view on cost versus value.
Nice to have
Built or ran 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.
- Competitive salary and eligibility for equity
- Biannual bonus scheme
- Fully expensed tech to match your needs
- Private health insurance
- Breakfast and dinner allowance for office-based employees As we hire globally, benefits may vary by location.
Requirements
- Track record of owning and shipping data products
- Track record of leading people
- Strong schema design for time series and event data
- Experience running production pipelines at scale
- Experience evaluating and negotiating with data vendors
Benefits mentioned
- equity
- Biannual bonus scheme
- Fully expensed tech
- Private health insurance
- Breakfast and dinner allowance
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