Use Python, SQL, graph databases, Docker, Kubernetes, and LLMs to own Kharon’s risk-propagation engine that evaluates entities in a knowledge graph and surfaces risk signals. The role spans research, data engineering, and product to evolve a production system for global security analytics.

Lead a team of DataOps and MLOps engineers building and evolving the ML platform and data operations for FDJ United’s Sportsbook product. You’ll work with AWS, Terraform, CloudFormation, Spark, Kafka, and CI/CD pipelines to enable end-to-end machine learning workflows from research to production.

FDJ UNITED★4.0 (96)· London

You'll lead a DataOps/MLOps team building an ML platform and data operations capability for FDJ United's Sportsbook, working with AWS, Terraform/CloudFormation, Spark, Kafka, and CI/CD pipelines for end-to-end ML lifecycle management. The role involves establishing best practices, monitoring, and governance while collaborating with Data Engineering, ML Engineering, Quants, and Data Science teams to personalize customer experiences and manage risk.

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.

Kingfisher★3.8 (77)· London

Senior Implementation Analyst at Kingfisher, working with GA360, GA4, Google Tag Manager, Tealium iQ, JavaScript, Tealium EventStream, Google Marketing Platform, and Google Cloud. You will design and implement tagging and measurement strategies for digital platforms, partner with Product, Data, and Analytics teams to drive optimisation, and manage tracking across websites and mobile apps.

You will lead a small cross-functional data pod building data pipelines, models and services in Python, SQL and Snowflake to turn supply chain data into customer-facing sustainability insights. The role combines hands-on data engineering with technical leadership and line management of the pod's engineers.

Databricks★3.0 (21)· London

You will work with Python, Scala, JavaScript/TypeScript, Apache Spark, and cloud ecosystems (AWS, Azure, GCP) to build production-grade data and AI solutions on the Databricks platform. In this hands-on role, you lead architecture and design decisions while embedding with customer teams to deliver end-to-end data pipelines, ML/AI models, and user-facing applications.

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.

You will design and build data pipelines, models, and services in Python and SQL, using Snowflake for warehousing. You will lead a small cross-functional data pod that transforms supply chain data into customer-facing insights for Sedex’s SaaS sustainability platform. This role includes line management of the pod’s engineers.

You'll design and maintain Y

**Python**, **SQL**, and **Snowflake** power the pipelines, models, and services this team builds to turn supply chain data into customer-facing insight. You will lead a small cross-functional data pod, combining hands-on engineering with line management of its engineers.

APL Logistics★3.3 (685)· London

You will work with Microsoft Fabric, Azure, Power Platform, ETL/ELT pipelines, APIs, and relational databases. This Regional Applications Team role manages data requests for EMEA and Americas, delivering data warehouses, pipelines, and automations for supply chain business users.

EPAM Systems★3.8 (703)· London

You will work with Python, SQL, GenAI frameworks (LLMs, RAG, LangChain, Hugging Face), cloud-native AI services (AWS, Azure, GCP), and MLOps tools such as Databricks or MLflow. As a consultant for EPAM, you will help clients shape and implement data-driven solutions, designing predictive models and GenAI-based applications to drive enterprise AI transformations.

You'll lead a 4–5 person team building machine learning systems using Python, TensorFlow, PyTorch, JAX, AWS, Docker, and Kubernetes for Super's Playstack platform, which powers sports betting and gaming experiences across Europe and Latin America. The role combines technical contribution, project management, and people leadership, focusing on predictive analytics, personalization, fraud detection, and real-time recommendations that enhance customer engagement in online gambling and sports betting.

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.

SavvyMoney★3.5 (2)· London

You will work with AWS Glue, Lambda, Step Functions, S3, Athena, Redshift, ECS, Spark, Java, and Python to build batch ETL pipelines and a cloud-native data platform. SavvyMoney provides integrated credit score and personal finance solutions to 1,600+ bank and credit union partners.

Python, Microsoft Azure, Docker, Azure Kubernetes, Apache Airflow, GitHub Actions, Snowflake, Databricks, and OpenAI LLMs. The role rebuilds data infrastructure and transforms financial data into research-ready datasets and signals for a fully systematic market-neutral equity fund.

Build and scale data pipelines for large video generation models using AWS S3, DynamoDB, Kubernetes, Python, and PyTorch. You will design annotation workflows across MTurk and Prolific, and train smaller supporting models for data filtering and quality assessment. Cantina Labs is a social AI company developing real-time character models.

You will use AWS Glue, Lambda, Step Functions, S3, Athena, Redshift, ClickHouse, and Amazon ECS to build batch and event-driven data pipelines for a financial technology company providing credit score and personal finance solutions. The work focuses on scalable ETL, analytical data modeling, and integration with Java-based backend microservices.

Head of Quality Engineering to own quality across the organisation, working with PHP, Kotlin, GO, Python, Typescript, React, React Native, GraphQL, Relay, PHPUnit, Behat, JUnit, Kotest, Jest, Maestro, K6, Datadog, Sentry, Incident.io, Grafana, AWS, Docker, Kubernetes, RabbitMQ, Argo, Github, and Github Actions. The role will lead the use of AI (LLMs) for testing and will manage a team of approximately two Quality Engineers while being hands-on with code and CI pipelines. Lendable builds technology for consumer credit and savings products.

You will work with Microsoft Azure, Azure Data Factory, Talend, Power BI, Tableau, Python, Java, JavaScript, CI/CD tools, and AI tools like Claude. As part of a data and AI consultancy, you will design modern data platforms and build ETL/ELT pipelines for clients across various industries.

UBS★3.8 (2.5k)· London

You will work with Python, Airflow, Prefect, Azure (AKS, EventHub, Terraform), Delta tables, DuckDB, Apache Spark, PostgreSQL, KDB, Docker, Kubernetes, JupyterHub, PowerBI, Streamlit, Marimo, and Java. You will lead the Credit Principal Algo Data team within UBS Global Markets, building and enhancing the trading analytics platform for automated eCredit trading.

Beamery★4.0 (1)· London

Beamery’s Data Engineering Team builds a self-service reporting and AI data platform, ingesting multiple sources into centralized infrastructure. The Senior Data Engineer leads ETL pipeline and analytics layer development, mentors engineers, and shapes the platform underpinning the company’s talent lifecycle management solutions.

You'll lead Python and FastAPI development on Lendable's Data Team, building data pipelines, APIs, and services deployed via Docker, Kubernetes, and AWS with ArgoCD. The fintech company rebuilds consumer finance products (loans, credit cards, car finance) to serve UK and US markets faster than traditional banks. You'll mentor a small team of 1–2 engineers while owning technical direction and remaining hands-on with code.

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.