Lead the EMEA Solutions Engineering team for Wise Platform, working with REST APIs (RESTful design, OpenAPI, OAuth2) and microservices architecture. The team helps top-tier banks and tech companies integrate Wise’s international finance products via their public API, providing post-sale technical consulting. You will build and mentor a high-performing technical delivery team, defining goals aligned with Wise Platform’s objectives.

You will build scalable server-side logic using JavaScript, TypeScript, and Node.js in a microservices architecture on AWS with Kubernetes, Terraform, Kafka, and Snowflake. You will join the MMH team within the Martech domain, which orchestrates campaign delivery across email, push notifications, and personalised content for all Sainsbury’s Group brands. The team includes 7 engineers.

Develop backend services using Node.js, Python, Java, C#, PHP, and Ruby on Rails, with databases including MySQL,

You’ll work with SQL, Python, Snowflake, AWS/GCP, and APIs to build and evolve the firm’s cloud-based data platform, developing scalable data pipelines and integrating data to support investment decisions. You will mentor two junior Data Engineers.

Wise★3.5 (42)· London

Lead a growing Solutions Engineering team in EMEA, providing technical consulting and product guidance to top-tier banks integrating Wise’s international finance products via REST API. Work with RESTful design, OpenAPI, OAuth2, and microservice architecture to architect integrations and influence the product roadmap.

You will own the dbt project (models, tests, CI/CD) and work with BigQuery (or Snowflake/Redshift), advanced SQL, and a BI tool like Looker or Metabase. As an Analytics Engineer for a £100m+ D2C e-commerce brand, you'll transform raw data into trusted dashboards that drive marketing, finance, and operational decisions.

Salesforce★4.2 (1.5k)· London

Success Architect works with Agentforce, Data Cloud, Salesforce Clouds, and data platforms like Snowflake, Databricks, AWS. They drive customer success by optimizing technical architecture for data unification and AI-driven automation, enabling personalized engagement and real-time decision-making.

Senior Data Engineer at Softwire, a UK digital consultancy, working with Python, SQL, Databricks, Snowflake, Fabric, and AWS/Azure/GCP across data architecture, pipeline design, and governance. You'll lead complex data engineering projects for clients across public and private sectors—from healthcare research platforms to energy market infrastructure—while mentoring junior engineers and shaping technical direction on multi-stakeholder engagements.

Virtusa★3.7 (1.1k)· London

Work with Snowflake, DBT, Python, SQL, and AWS services to build enterprise data platforms. The role supports a global pharma engagement, designing scalable data solutions for advanced analytics, clinical insights, and business intelligence.

Snowflake, DBT, Python, SQL, and AWS. Leads architecture of enterprise data platforms for a global pharma engagement supporting clinical insights, business intelligence, and data governance.

Work with SQL, Python, and modern data technologies (dbt, Spark, containers, DevOps tooling, orchestration tools, Git, AI/ML). As a Solution Engineer for the UK market, you present Snowflake’s technology and vision, working hands-on with prospects to demonstrate value through demos, proof-of-concepts, and design.

You will work with Core Java, Aeron, FIX, SBE, Artio, Linux, and performance profiling tools. You will join a team developing a high-performance electronic trading platform with a focus on microsecond-level latency. The role requires 5+ years of Core Java experience and 2+ years in ultra-low-latency systems.

Develop low-latency server-side Java components for a global eTrading and eRisk platform serving FX and electronic execution. You’ll work with enterprise messaging (multicast, low-latency), FIX protocol, kdb+, and apply CI, TDD/BDD. The team builds distributed systems for pricing, order execution, and algorithmic trading.

Use Java, Python, Kafka, and RESTful APIs to build cloud-ready, distributed applications with relational/NoSQL databases and caching (e.g., Memcached). You will transform middle-office workflows at PIMCO, a global asset manager, building data infrastructure and reporting to improve investment teams’ access to positions, P&L, and performance data.

Work with Microsoft Fabric, Databricks, Azure, Snowflake, Python, Spark, SQL/NoSQL, PowerShell, Azure Data Factory and Azure DevOps to build a Fabric Data Lakehouse for USS’s Investment Management business, implementing scalable ETL/ELT frameworks across a medallion architecture. Share knowledge across a small team of data engineers and collaborate with architects, business stakeholders and data teams.

You will work with Azure DevOps Pipelines, CI/CD, Atlassian Confluence, Jira, PowerShell, Python, C#, SQL, and cloud deployments to Microsoft Fabric/Synapse/Azure, Snowflake, Power BI, and application security tools. You will help build automation, CI/CD pipelines, and release processes for in-house developed solutions at the Universities Superannuation Scheme pension scheme.

Use Python, Azure, Docker, Kubernetes, Apache Airflow, and GitHub Actions to build scalable ETL pipelines, financial data pipelines, and cloud-native infrastructure. This front-office role is at a systematic equity hedge fund modernising its quantitative research platform, working directly with portfolio managers and researchers. Experience with S&P Xpressfeed, Snowflake, Bloomberg, MSCI Barra, Databricks, and LLMs is advantageous.

You will work with Python, LLMs, agentic workflows, retrieval-augmented generation (RAG), and internal AI platforms. The Tactical AI Automations team deploys and supports AI tools across PIMCO's Portfolio Management and Analytics groups, including operational support for Lane Assist and POET (portfolio optimization tools).

You will work with Python, PowerShell, SQL, OMS/EMS platforms (FlexTrade, Triton, SpiderRock), Linux, Windows, cloud (AWS/Kubernetes), FIX, messaging systems, market data flows, and monitoring tools like Geneos/Zabbix. As part of a global hedge fund’s front-office technology team, you will directly support equity portfolio managers, traders, and analysts to ensure the reliability and performance of business-critical trading systems.

Rebuild data infrastructure for a market-neutral systematic equities fund using Python, Microsoft Azure, Docker, Azure Kubernetes, Apache Airflow, and GitHub Actions for CI/CD. Work on ETL pipelines, vendor integration, and cloud-based research platforms, with relevant experience in Snowflake, Bloomberg, MSCI Barra, or Databricks. The role spans data engineering and quantitative development to transform financial data into investment signals.

HCLTech★3.7 (11k)· London

Work with Quantexa Decision Intelligence Platform, Spark/PySpark, Python/Scala, and Big Data (Hive/HDFS) to design and develop data ingestion, transformation, and ETL pipelines. Focus on entity resolution, network analytics, and graph-based data models for analytics use cases.

NatWest Group★3.7 (1.2k)· London

You'll work with Mainframe hardware (DASD, SAN/FICON, IBM z), automation scripting (Python/Shell), infrastructure as code, GDPS, and CI/CD pipelines. As part of NatWest Digital X, you'll engineer hardware solutions for the Mainframe environment, applying automation to improve products. This technical lead role guides a team but no team size is specified.

Luxoft★4.5 (669)· London

Lead Python engineer designs, builds, and maintains risk engineering systems for a global commodity trading company, working on commodities risk and market data pipelines. Uses Python, AWS/GCP/Azure, CI/CD, containerization, and AI-assisted tooling. Collaborates with quants, traders, and risk managers in a high-velocity delivery environment.

You'll build scalable data infrastructure for AI applications using Python, SQL, Spark, dbt, LangChain, and cloud platforms (AWS, Azure, GCP), working with data pipelines, embeddings, vector search, and LLMOps tools like Terraform and LangSmith. QuantumBlack, McKinsey's AI division, develops next-generation AI systems and enterprise solutions for clients across industries. You'll collaborate with Data Scientists and ML Engineers in cross-functional Agile teams based in London, supporting the firm's AI adoption and complex problem-solving at scale.