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Genomics

Product Engineer

London; OxfordHybrid · United Kingdom
FullTime · Genomics
POSTED 23 SEPT
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Role
51 days opentrue age
Posted 23 Sept
Pay
£70k–£138kno pay posted
Market p25–p75
£70k–£138k
London · n=119 · 365d to 12 Nov
CompanyGenomics →
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37,487open · Software engineering
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Location: Oxford or London (Hybrid)

The Mission: Why We Exist

Genomics is a science-led transatlantic TechBio combining large-scale genetic and health data with proprietary analytics to accelerate drug discovery and advance predictive, preventative healthcare. We are united by a single vision to help people live longer healthier lives, using the power of genomics.

Genomics aims to help people live longer, healthier lives in two ways: super-charging drug discovery and development for novel treatments with our AI-enabled advanced genetic analytics platform, and by helping people understand their personal risk of common chronic diseases through polygenic risk scores - giving doctors and health systems the chance to get the right people into the right prevention, screening and treatment programmes at the right time.

Role Purpose

Genomics runs on multi-trillion-row, petabyte-scale genetic and health data. Mystra is the analytical data platform that makes that usable, and MystraAI is the agentic layer we're building on top of it. This is a Staff-level role for someone who wants to push the boundaries of what a data platform can do — solving hard, novel infrastructure problems at genuine scale, and setting the technical direction that other teams build on.

You'll lead the analytical data platform and our Data-as-a-Service offering, shape the data foundations behind MystraAI, and line-manage a small team of engineers while staying deeply hands-on. If you want your work to sit at the intersection of large-scale systems engineering and genuinely meaningful science, this is it.

A Day in the Life

The role spans the full depth of the platform — from database internals up to the systems that serve data across the product. On any given day you might be:

Pushing multi-tenant ClickHouse (or equivalent OLAP) clusters to their limits at multi-trillion-row, petabyte scale — designing sharding and replication strategies, building materialised views, and solving genuinely hard performance and cost/efficiency problems most engineers never get to touch.

Building the tooling and automation that lets data-intensive pipelines scale themselves — smart observability, predictive capacity planning, and systems resilient enough that incidents become rare rather than routine.

Shaping Data-as-a-Service as a real product — designing a secure, multi-tenant, immutable release architecture, with data made discoverable at scale through catalogue and ontology-driven search, in partnership with the data team.

Powering agentic AI from the data platform — architecting the data foundations behind MystraAI and designing secure, tenant-scoped access patterns for autonomous agents, partnering closely with the ML team on how our AI systems perform.

Treating security as a design problem, not a checklist — building tenant isolation, credential management and least-privilege access into the architecture from first principles.

Setting technical direction, mentoring engineers, and influencing decisions well beyond your own team.

Who You Are

You're a recognised specialist who leads through expertise — principal-level individual-contributor depth combined with the judgement to set standards others follow. You'll bring:

Large-scale OLAP / ClickHouse. Deep experience designing and pushing multi-tenant ClickHouse at extreme scale. You engage with the engine at source level rather than as a black box — and ideally have contributed code upstream.

Platform engineering at scale. You've built self-healing, observable systems for analytical data platforms and pipelines — the kind of engineering that reduces toil rather than manages it.

Data-as-a-Service productisation. You think in terms of data as a product: secure, multi-tenant, immutable releases, and discoverability at scale.

Agent-ready data. You understand what it takes to expose platform data to agents safely and at scale — access patterns, tenant isolation, sensible guardrails — and have scaled data infrastructure under demanding workloads.

Multi-tenant security. You design for isolation, least-privilege access and sound secrets management from the outset.

Source · GenomicsFirst seen 4 NovOriginal ↗