Join Squid as a founding data engineer to build the production-grade foundations of our grid modeling platform. You will design scalable data models and high-integrity pipelines that unify messy legacy infrastructure data into an auditable source of truth, enabling humans and AI agents to modernize national power systems safely and efficiently.
Software Engineer (Data Platforms) at Squid
Grid planning is the primary bottleneck for the energy transition, and Squid is fixing it with an agentic modelling platform. As one of the first engineers at this YC-backed London startup, you'll build the data foundations that unify messy infrastructure data into an auditable source of truth. Working alongside founders from National Grid and AWS, you will design the pipelines and models that power the future of national power systems. If you want to solve complex data problems that have a real-world impact on electrification and grid modernization, this is the role for you.
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Location
London, United Kingdom
Compensation
£75k-£200k + Equity
Company
Squid
Role overview
Squid (squid.energy) is an energy technology startup that builds an AI-powered, browser-native grid planning platform for electric utilities and other grid operators.[13][12][9] The product provides a single, live and versioned network model—a detailed grid map of substations, lines, projects, and policies—with evidence attached, so that planning workflows are consistent, auditable, and faster to execute.[13][9][5] Utilities can model the electricity network, run stress tests and scenario analyses, and manage network data and planning decisions in one place, enabling AI-driven planning for power grids and improving accessibility and usability of electricity network data across the energy sector.[13][12][9][5][8] The company focuses on helping distribution and transmission operators modernize grid planning, accelerate infrastructure deployment, and unlock progress in the transition to a more complex, low‑carbon energy system.[9][10][5]
What you will do
- Build production data pipelines and DAG-based orchestration systems to ingest, transform, and validate complex, inconsistent technical and geospatial grid datasets.
- Design scalable data models and storage systems that serve as a versioned, auditable source of truth for power grid modeling and decision-making.
- Develop APIs and services that integrate processed data into agentic AI systems, ensuring high-quality foundations for collaborative human-AI grid planning.
Who this is a fit for
- Strong professional experience in Python and SQL, with a proven track record of building and maintaining production data pipelines and DAG orchestration.
- Expertise in designing complex data models, schemas, and transformation layers, particularly when dealing with messy, incomplete, or poorly documented source data.
- Solid software engineering fundamentals including testing, code review, and maintainable system design, with a deep interest in applying AI to technical engineering problems.
Why this role is remarkable
- Join as one of the first engineers at a YC-backed company tackling the critical infrastructure bottleneck preventing the global transition to clean energy.
- Work directly with founders from National Grid, Octopus Energy, and AWS while partnering with industry giants like National Grid and Northern Powergrid.
- Shape the entire data architecture from the ground up in a high-ownership role that combines data engineering, software design, and applied AI.
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