Work with Java/Spring, React, JavaScript/TypeScript, CI/CD pipelines, and distributed systems. You'll join the Account Integrity team building a globally scalable fraud prevention engine to protect customer accounts and prevent financial crime using machine learning and real-time monitoring.

Wise★3.5 (42)· London

You will build and refine financial crime prevention systems using Java (or JVM languages) with Spring, React/JavaScript/TypeScript, and CI/CD pipelines, working 80% backend and 20% frontend. You join the Account Integrity team, which protects Wise’s global platform against fraud via machine learning and real-time transaction monitoring, and you will own projects end-to-end.

Build scalable distributed systems with Java (Spring/Spring Boot) and Python, using Kafka, MQ, XML, and CI/CD in Unix/Linux environments. This Risk Services team within CRISIL supports capital-markets risk data ingestion, processing, analytics, and reporting for Global Markets.

You'll build distributed backend services and microservices using Java (Spring/Spring Boot), Python, messaging frameworks like Kafka/MQ, and Unix/Linux, with CI/CD and containerization. The Role sits on the Risk Services team within Global Markets, designing scalable systems for risk data processing, analytics, and reporting workflows.

SQL, MySQL, PostgreSQL, Doris Event, QuickSight, and possibly Amplitude, Mixpanel, GA4, Airbridge, Adjust, Airflow, dbt, Git or Python. You will own analytics schema, data models, and BI dashboards for ZYMIX, a Gen Z social super-app launching in the UK, bridging product analytics with data building.

This role develops generative AI applications using Java, Python, React or Angular, LangChain, LlamaIndex, Hugging Face, Docker, Kubernetes, and AWS, with tools like GitHub Copilot. You will build scalable, AI-powered solutions for Citi’s global finance operations.

Wise★3.5 (42)· London

Build backend

Wise★3.5 (42)· London

You will work with Java, Kotlin, Spring Boot, AWS, PostgreSQL, Apache Kafka, and RESTful APIs. The Recurring Payin team builds the Direct Debit API platform that powers automated payments and scheduled top-ups into Wise, including a payment orchestration system routing across providers.

Fivetran★3.3 (8)· London

Senior Sales Engineer working with AWS, GCP, Azure, Snowflake, BigQuery, Databricks, Kubernetes, Docker, Podman, Grafana, Linux, Windows, Python, Java, and databases like Oracle, SQL Server, Postgres, MySQL, and NoSQL. The role supports Fivetran’s Commercial sales team by understanding customer data replication needs and leading proof-of-value processes for the company’s automated data pipeline and transformation solutions.

Durlston Partners· London

You'll use Java, Spring Boot, Kafka, and AWS (EKS, S3), plus PostgreSQL, SQL Server, and CI/CD. The team builds the core trade processing, reconciliation, and reporting platform for a leading systematic hedge fund’s multi-asset trading, collaborating closely with traders and quants.

Connected Places Catapult★3.0 (2)· London

You will apply statistical analysis, machine learning, AI, and generative AI (LLMs, agentic workflows) using Python, and work with R, Java, Terraform, and C++. As a Consultant Data Scientist, you deliver digital and data solutions to accelerate innovation for public bodies and infrastructure providers in transport and the built environment. You operate within a project-based team under guidance of a Head of Applied Data Science.

You will work with Java, Spring Boot, Kafka, and stream processing to build the backend for customer-facing spending summaries, travel insights, and spend controls. This is for the early-stage Account Insights team at Wise, a global technology company building a network for moving money internationally.

You'll work with Java/Spring Boot, Kafka, and stream processing to build the backend powering customer-facing insights—spending summaries, travel insights, and spend controls. This is on the early-stage Account Insights team at Wise, a global technology company building the best way to move and manage money.

Goldman Sachs★3.9 (2.3k)· London

You will work on backend micro-service development using Java, Spring, and MongoDB. At Goldman Sachs, a global investment banking and securities firm, you’ll build scalable software, low-latency systems, and data-driven solutions for trading, sales, and asset management.

Wise★3.5 (42)· London

You will build the backend for customer-facing insights (spending summaries, travel insights, budgets, recurring-payment tracking) using Java, Spring Boot, Kafka, and stream processing across a high-throughput streaming and storage stack. The Account Insights team aggregates transaction activity data into low-latency APIs and handles categorisation accuracy.

Sainsbury’s★3.5 (16k)· London

In this Senior Data Engineer role you will design and build scalable data pipelines and platforms using PySpark or PyTorch on AWS EMR, Snowflake, Docker, Airflow, Kubernetes, SQL/NoSQL databases and CI/CD with GitHub Actions. You will partner with Data Scientists to make data reliable and production-ready for machine learning solutions, and mentor junior and mid-level engineers.

Design, develop, and optimize data pipelines using SQL, Python, Scala, Java, or Spark, along with ETL/ELT tools like Azure Data Factory, AWS Glue, and Apache Airflow, on cloud platforms such as Azure, AWS, or GCP. You will work with databases (SQL Server, Snowflake, MongoDB), big data technologies (Spark, Kafka, Databricks), and orchestration tools to build scalable cloud-based data platforms supporting enterprise analytics and machine learning.

Build and scale real-time pipelines, analytics infrastructure, vector databases, and data workflows for an AI assistant that automates property management operations. Work with Python, Apache Spark, Airflow, Kafka, Elasticsearch/OpenSearch, MongoDB, vector databases (Qdrant, Milvus, pgvector), Pandas, and Polars. This is an early data hire with input into architecture decisions.

Citi★3.9 (21k)· London

Build and scale AI-powered financial systems using Java, Spring, React/Angular, Python, FastAPI, Docker, and GitHub Copilot within Citi’s global tech environment. You will design generative AI agents, LLM workflows, and RAG pipelines while working on enterprise microservices, mobile, or front-end development. This role is for an individual contributor on an agile team.

You'll work with Python, FastAPI/Flask/Django, PostgreSQL/MySQL, Databricks, Azure cloud infrastructure, and CI/CD tools to build data pipelines and APIs for Breathe's battery management platform. The Platform & AI team processes time-series battery test data, automates analysis with AI, and provides infrastructure supporting R&D, product development, and service delivery across the company's physics-based battery management software used by major automotive and electronics brands.

Lead a data engineering team owning the Snowflake and dbt

Design and build data ingestion pipelines, ETL/ELT processes, and scalable data models using Python, SQL, Apache Spark, Kafka, Airflow, Dagster, Docker, and Kubernetes. The role contributes to a scalable data platform powering analytics, business intelligence, and product development.

You will work with SQL, Python, Apache Kafka, Apache Spark, PostgreSQL, MySQL, Git, CI/CD, Docker, and Kubernetes. You will develop and maintain modern data platforms—building data pipelines, ETL/ELT processes, and scalable data models—to support reporting, analytics, and operational systems for a well-established UK organisation.

Work with Snowflake, dbt, CI/CD, and SQL to lead the data platform that connects product, growth, finance, and CX to a single source of truth, also supporting AI tooling across the company. No team size is stated.

Build data pipelines using Python, SQL, MySQL, Snowflake, AWS, REST APIs, webhooks, CDC, and Microsoft SQL Server, integrating healthcare standards HL7 v2 and FHIR. The pipelines ingest and transform clinical data from EHR systems to power Circadia’s AI-driven platform that predicts early signs of patient deterioration. You report to the CTO and collaborate with backend and ML engineers.