Lead ClickHouse Engineer

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Reactive Markets

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2019

💳 Fintech

🤝 B2B

💸 Finance

Fintech • B2B • Finance

Reactive Markets is a financial infrastructure company that provides ultra-low-latency connectivity and execution for institutional trading across FX, equities and other asset classes. Its network connects clients to 35+ liquidity providers with deterministic sub-50 microsecond end-to-end latency, accessible via a single API, UI, or integrations with EMS/OMS/pricing engines. The platform is engineered for bilateral trading, systematic and manual strategies, and offers real-time latency reporting, analytics, global deployment (New York, London, Singapore), and FCA-regulated services for professional market participants.

📋 Description

• Cluster operations at scale — running, upgrading and evolving a multi-AZ ClickHouse estate on Kubernetes, with rehearsed backup and recovery • Schema and query engineering — table and sorting-key design, partitioning, materialised views, and query optimisation against multi-terabyte datasets • Capacity and observability — a measured capacity model, storage tiering and retention, and the Grafana monitoring and alerting that keeps the plant's health visible • Ingestion and data quality — correctness and completeness gates on the pipelines feeding the plant; reconciliation that proves nothing was dropped • Workload isolation — keeping ingest, operations, reporting and ad-hoc analytics from treading on each other as read load grows • Team and knowledge leadership — mentoring the engineer(s) working on the estate, setting standards for runbooks and documentation, and making the plant supportable by the team, not the author • AI-assisted operations — modern tooling (including MCP-based AI access to the estate) that lets a small team run a large platform well

🎯 Requirements

• Columnar/OLAP database engineering — ClickHouse strongly preferred; deep experience with another columnar or large-scale time-series store (BigQuery, Redshift, Druid, kdb+ or similar) also works • A track record of owning architectural decisions for a production data platform, not just operating within one someone else designed • SQL depth — execution plans, query optimisation, and schema design for very large datasets • Operational/SRE experience — you have carried production responsibility for a data platform: monitoring, capacity, incidents, recovery • Linux and Kubernetes — comfort with the operational layer beneath the database • A programming language — one of Python, Go, R, or MATLAB (Python preferred) • Engineering discipline — you write proposals, strategies, and architectural documents and diagrams well, and you manage change properly • Git — excellent version-control practice • Distributed-systems fundamentals — replication, consistency, failure modes • Financial services experience is a plus but not essential — domain knowledge can be learned; operational instinct cannot

🏖️ Benefits

• A serious estate — genuine scale, genuine criticality: the system of record for a live trading network, not a reporting sidecar • Real ownership — architectural and technical leadership of a business-critical core platform • An excellent team — senior engineers who care about craft, collaborate openly, and hold each other to high standards • Sustainable operations — follow-the-sun coverage by design; on-call is shared, contracted and planned, not heroics • Competitive package — competitive compensation and benefits aligned to your local market • Modern tooling — AI-assisted operations and investigation tooling that removes toil rather than adding process • Growth — the estate is scaling to multiples of today's volume; the role grows with it