Data Engineer

Refractal; Greater London; In loco; GBP 90.000 - 130.000; Tempo pieno

Descrizione del lavoro

Refractal is a UK-based AI security company seeking a data engineer to build the data foundation and evidence store relied upon by customers' auditors. You will shape the data model, implement streaming and batch pipelines, and own data quality, residency, and retention for regulated customers.

You will collaborate with data scientists and security engineers to create training datasets and provenance, ensuring compliant reporting against EU AI Act, NIST RMF, and ISO standards.

Competenze

• 6+ years of experience in data engineering or similar field.
• Strong Python and SQL proficiency.
• Experience with streaming data pipelines (Kafka, Pub/Sub or similar).
• Data modelling for audit trails, lineage and multi-tenant isolation.
• Security-minded handling of sensitive data.
• Competitive equity to share in Refractal's growth.

Mansioni

• Design the data model for the evidence store.
• Build the streaming and batch layers that turn ingested activity into queryable data.
• Own data quality, retention, residency and deletion controls for regulated customers.
• Build training and evaluation datasets with data scientists and security engineers.
• Make compliance reporting quick to produce from data.

Conoscenze

Python

SQL

Data engineering

Streaming data

Data modelling

Security-minded data handling

Equity ownership

Strumenti

PostgreSQL

BigQuery

ClickHouse

Descrizione del lavoro

Visa sponsorship / work permit support is mentioned in the posting. Relocation support is mentioned in the posting.

Refractal is an AI security company building the infrastructure organisations need to defend against autonomous AI threats. 2026 has shown that generally capable intelligence is here. The challenge now is modernising security to stop AI-enabled threats, whether they come from internal agents going rogue or from attackers using AI to become more dangerous.

Refractal was founded on cybersecurity and AI expertise from MIT, Microsoft, NASA and the U.S. Navy. Our product lets organisations detect AI-enabled threats at low cost without sacrificing detection quality. We take a practical approach to AI risk, combining proven cybersecurity methods with frontier AI security research.

Today, we work with governments and organisations that can't afford to get security wrong. We're backed by leading deep-tech and cybersecurity investors and are growing the team to deliver on this mission.

You'll build Refractal's data foundation, including the evidence store that customers' auditors rely on, the analytics behind compliance reporting and the datasets our models are trained on.

• Design the data model for our append-only, cryptographically signed evidence store.
• Build the streaming and batch layer that turns ingested activity and detections into queryable data, working with our integrations engineers on schemas.
• Own data quality, retention, residency and deletion controls for regulated customers.
• Build training and evaluation datasets with our data scientists and security engineers.
• Make compliance reporting against the EU AI Act, NIST AI RMF and ISO/IEC 42001 quick to produce from our data.

Success in your first six months

• The evidence store is in production, documented and trusted by customers' auditors.
• Colleagues answer compliance and detection questions from data you own, without ad hoc work.
• Training and evaluation data has clear provenance and separation.
• Data work in banking, insurance or other regulated industries.
• Experience with UK GDPR and data residency.

Our values

Radical transparency. We believe the best work happens when everyone feels able to give and receive honest, constructive feedback.

Public service. We see AI security as a form of public service. Getting the AI transition right means putting the right infrastructure in place to manage the threats that come with it, and our work helps protect the institutions and services society depends on.

Fail fast. We test ideas early, seek feedback and learn quickly. We experiment rapidly and change course when something isn't working, without compromising on security.

Pragmatism, not dogmatism. We choose approaches based on how well they solve the problem. That means combining established cybersecurity methods with frontier AI research, questioning our assumptions, and changing our minds when the evidence changes.

• 6+ years in data engineering, owning production pipelines.
• Strong Python and SQL, with Postgres plus a warehouse or analytics store such as BigQuery or ClickHouse.
• Experience with streaming (Kafka, Pub/Sub or similar) and orchestration (Airflow, Dagster or similar).
• Data modelling for audit trails, lineage and multi-tenant isolation.
• Security-minded handling of sensitive data.
• Competitive equity to share in Refractal's growth