Lead ClickHouse Engineer

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Reactive Markets

WebsiteLinkedInAlle Stellen

11 - 50 Mitarbeiter

Gegründet 2019

💳 Fintech

🤝 B2B

💸 Finanzen

Fintech • B2B • Finance

Reactive Markets ist ein Finanzinfrastrukturunternehmen, das Konnektivität und Ausführung mit extrem niedriger Latenz für institutionellen Handel in den Bereichen FX, Aktien und anderen Anlageklassen bereitstellt. Sein Netzwerk verbindet Kunden mit über 35 Liquiditätsanbietern mit einer deterministischen End-to-End-Latenz von unter 50 Mikrosekunden, zugänglich über eine einzelne API, Benutzeroberfläche oder Integrationen mit EMS/OMS/Pricing Engines. Die Plattform ist für bilateralen Handel, systematische und manuelle Strategien konzipiert und bietet Echtzeit-Latenzberichte, Analysen, globale Bereitstellung (New York, London, Singapur) und FCA-regulierte Dienstleistungen für professionelle Marktteilnehmer.

Beschreibung

• 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

🎯 Anforderungen

• 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

🏖️ Vorteile

• 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