Data Engineering Jobs

Palantir Technologies · New York, United States · US$100,000 – US$145,000 pa

Builds and maintains data pipelines, reporting datasets and dashboards that support Recruiting and Hiring Operations, integrating systems such as Lever, Workday and Foundry. Works cross-functionally with recruiters, data, security and privacy partners, moving between pipeline work, integration debugging, documentation and stakeholder enablement.

Palantir Technologies · New York, United States · US$145,000 – US$155,000 pa

Works deep inside the data processing infrastructure behind Palantir Foundry, covering query plan optimization, operator execution, and efficient data reads and writes. Extends open-source engines and table formats including Apache Spark, DataFusion, and Iceberg, taking changes through design, code review, testing, and release. Correctness, compatibility, and predictable performance are central to the work.

eFinancialCareers · London

Join the EMEA Reference Data team within Global Markets Technology, building and owning critical components of a reference data platform used across a tier-one investment bank. Work in Scala with RDF, SPARQL and Big Data technologies such as Apache Hadoop, following Agile and covering the full software development lifecycle, including key regulatory programmes.

eFinancialCareers · London · £700 pd

Lead end-to-end technology delivery of Counterparty Credit Risk change across EMEA, turning the CCR Product Owner roadmap into executable plans and production outcomes. Coordinate risk calculation engines, exposure and limit platforms, trade and market data feeds, reference data, reporting and downstream integrations, running Agile practices with disciplined programme governance. Requires deep CCR domain knowledge spanning SA-CCR, IMM, CVA, PFE, margining and collateral.

Grafana Labs · United Kingdom · £103,958 – £124,750 pa

Backend-focused role on the Grafana Alerting squad, working at the core of the open-source Grafana project and the SLOs product. Engineers design, build and operate distributed systems that scale Prometheus-based alert ingestion, evaluation and delivery, including systems reaching over 500 evaluations per second in production, with on-call ownership and mentoring duties.

Palantir Technologies · Palo Alto, United States · US$135,000 – US$145,000 pa

Build, operate and maintain high-performance, scalable services across Palantir platforms and government deployments. Day-to-day work spans monitoring, configuration management, upgrades, migrations, debugging production issues, on-call support, and automating manual workflows using Java, Go, Python or JavaScript.

Palantir Technologies · London

Contributes high-quality code to the shared infrastructure behind Palantir Foundry, Gotham and Apollo, spanning backend, developer, frontend and storage infrastructure. Work includes a Kubernetes-based PaaS, secure fleet-wide deployment tooling and observability systems, in small engineering teams building tools for other developers.

Palantir Technologies · London

New-grad engineers contribute production code to the shared infrastructure behind Foundry, Gotham and Apollo, spanning backend, developer, frontend and storage infrastructure. Teams work on a Kubernetes-based PaaS, fleet-wide deployment tooling and observability systems, building tools used by other developers.

Palantir Technologies · London

Works deep inside the data processing infrastructure behind Palantir Foundry, designing query planning and optimization, extending execution engines, and improving operators, parallelism and memory management. Builds on and extends Apache Spark, DataFusion, Comet, Velox and Iceberg, owning changes from design through production with a high bar for correctness and predictable performance.

eFinancialCareers · London · £200,000 – £500,000 pa

Engineers design and build large-scale distributed systems for quantitative trading and research infrastructure, spanning compute scheduling, storage, real-time event-driven systems, messaging, fault tolerance and state replication. Teams are small with significant ownership, working on petabyte-scale data and HPC/CPU/GPU workloads where performance and reliability gains have immediate measurable impact.