Head of Data & AI

Head of Data & AI at Volteras — own the data platform, lead ML product development, and scale real-time EV telemetry infrastructure. Remote or London.

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Responsibilities:

Own the unified data model and partner data contracts, ingestion and transformation pipelines, analytics architecture, schema and query design, data quality, and data governance

Set the vision and multi-quarter roadmap for the data platform, making deliberate build-vs-buy calls and keeping it scaling with the business

Lead the build of the intelligence layer — using machine learning to surface actionable insight from raw telemetry: fleet health, early fault detection, and cost and value signals

Own reliability standards (durability, recoverability, availability) and cloud cost and capacity trade-offs, working alongside the Head of Platform

Own governance frameworks: data classification, lifecycle and retention, access and consent, and GDPR/PII obligations for sensitive telemetry

Enable internal decision-making with solid analytics and BI while keeping the data that is the product coherent and trustworthy

Bring a data voice to commercial and exec decisions: company strategy, pricing and packaging, and partnerships

Grow and lead the data team

You will own data end to end at Volteras — an API platform connecting fleet operators to real-time vehicle data, scaling globally in a fast-moving market.

You're joining a working platform, not building from scratch. Live ingestion from multiple OEMs runs in production through a managed streaming layer, a unified data model serves a live public API and customer portal, and analytics is already split out via CDC into a separate BI database. Your job is to mature and scale it.

As Head of Data & AI you will set the multi-quarter roadmap, make the build-vs-buy calls, and lead the build of our intelligence layer. Today we move data reliably — next we make it intelligent, using machine learning to turn raw telemetry into insight customers can act on. You will also lead and grow the data team, starting with the data engineer already in place. This is a hands-on leadership role: you set strategy and stay in the codebase.

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Requirements:

Hands-on data leader — you set strategy and stay in the codebase, designing schemas, building pipelines, and making architectural calls

Strong data modelling experience across messy, federated sources: turning fragmented, conflicting inputs into one coherent model the whole company builds on

Experienced running real-time streaming pipelines at scale — Kafka, Kinesis, MSK or equivalent — including contract management, delivery guarantees, replay, and handling upstream failures

Deep PostgreSQL expertise at high volume: partitioning, time-series patterns, query and index tuning, and a clear view on self-managed vs managed tradeoffs

Comfortable with transformation tooling (dbt) and orchestration (Airflow), and clear on where CDC-into-replica patterns stop scaling

A machine learning practitioner who has built and shipped ML on real-world data, from feature engineering through to productionised models

Serious about data quality and reliability — freshness and correctness as first-class SLAs, with real monitoring and lineage in data ops pipelines

Experienced with data governance and privacy under GDPR, ideally in a regulated or contractual B2B setting

Track record building and leading data teams: setting priorities and turning strategy into scoped, sequenced work engineers can deliver

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The connected vehicle data platform

Our collaborative approach ensures your integration is perfectly aligned with your use case. Begin a partnership built on reliable, OEM-grade connected vehicle data.

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