Data Engineering Jobs

Palantir Technologies · London

Builds the lowest layers of Palantir's Foundry and Gotham platforms, spanning database technologies, distributed systems, large-scale data, security and application infrastructure. Work includes designing opinionated APIs, tracing performance in high-scale microservice architectures, and automating systems like Cassandra, Elasticsearch and Kafka.

Palantir Technologies · Washington, United States · US$135,000 – US$200,000 pa

Forward Deployed Software Engineers embed directly with federal health and civilian agency customers, rapidly diagnosing hard problems and building end-to-end solutions. Work spans whiteboarding architecture, data pipelines, operational workflows, AI agent deployment, and advising executives, often within small high-ownership teams. Technologies include Python, Java, TypeScript/React, Spark, and AWS.

Harnham - Data and Analytics Recruitment · Newcastle upon Tyne · £84,000 pa

Own and oversee a business-critical enterprise data platform built on Microsoft Azure, acting as technical lead for architecture, scalability, governance and operational excellence. Work with Infrastructure, Security and Architecture teams on CI/CD, automation, monitoring and Infrastructure-as-Code, supporting production and incident management while enabling Data Engineers and shaping platform strategy across Data and AI initiatives.

eFinancialCareers · London · £70,000 – £106,000 pa

Designs and builds a greenfield data platform in a hybrid Azure and on-prem environment, creating pipelines, ETL processes and data models while migrating legacy capability. Works within a circa 100-person EMEA Data & Analytics Technology team, mentoring peers and aligning delivery to platform strategy. Requires at least two days a week in the London office.

eFinancialCareers · London · £700 pd

Hands-on role building AI-powered applications, intelligent workflows and machine learning solutions in Python, taking them from concept through to enterprise production deployment. Involves LLMs, agentic frameworks, AI orchestration, model evaluation, testing and monitoring, working with technical teams and business stakeholders to drive AI adoption.

Palantir Technologies · Washington, United States · US$135,000 – US$200,000 pa

Builds and evolves APIs powered by Kubernetes controllers, abstracting complex distributed systems so government and vendor developers can deploy microservices into a secure, infrastructure-agnostic runtime. Works with forward-deployed and customer engineers to close product gaps, and champions a long-term roadmap for scalability and reduced operational burden.

Palantir Technologies · New York, United States

Builds the lowest layers of Palantir's Foundry and Gotham platforms, focusing on database technologies, distributed systems, large-scale data, security and application infrastructure. Work spans performant search and indexing, open-source data processing libraries, container scheduling and opinionated APIs, using Java, Rust, Go, Cassandra, Elasticsearch, Kafka and Kubernetes.

Palantir Technologies · New York, United States · US$135,000 – US$200,000 pa

Builds and evolves APIs powered by Kubernetes controllers, bridging raw clusters and an infrastructure-agnostic runtime for hundreds of microservices. Works with forward deployed and customer engineers on a PaaS for US Government customers, shaping the product's early strategy and long-term tech roadmap.

Palantir Technologies · New York, United States · US$110,000 – US$147,000 pa

Ensures stability and reliability of mission-critical workflows built on Palantir software, going on call to resolve incidents before customers are impacted. Uses field learnings to drive product change, shape internal tooling, and automate or streamline workflows, documenting best practices to raise reliability across the organisation.

Palantir Technologies · New York, United States · US$135,000 – US$200,000 pa

Works directly with customers to own Gen AI strategy and implementation, building end-to-end LLM workflows and taking them to production at large scale. Operates like a hands-on AI startup CTO in small teams, delivering high-stakes projects and feeding field learnings back into the AIP product suite. Requires strong engineering and ML foundations plus up to 25% travel to client sites.

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.

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.

eFinancialCareers · Belfast · £45,000 – £60,000 pa

Hands-on role building and maintaining ETL/ELT pipelines, data warehouses and data lakes, with a focus on Microsoft Fabric, SQL Server, SSIS and SSRS, plus tools like Fivetran and Alteryx. You'll take ownership of the data engineering function, support data migration from legacy systems and work closely with analysts, scientists and business stakeholders.

eFinancialCareers · London · £108,000 – £162,000 pa

Sets up and leads the EMEA cross-domain data architecture function, covering domains such as Party, Product, Transaction, Risk, Finance, Compliance, Operations and HR. Drives data domain and data product thinking, target-state architecture, governance and standards, and supports strategic programmes including the Data Platform, Client Lifecycle Programme, ECB and BCBS 239. Works with business and IT stakeholders and global domain architects, using tools such as Collibra, Axon, Purview, Databricks and Snowflake.

eFinancialCareers · London

Bridge the gap between traders and the data engineering team at an alternative investment manager, operating across the full data lifecycle from requirement gathering to delivery. Translate complex trading strategies into scalable data engineering requirements using market and alternative datasets across multiple asset classes, with SQL and Python.