Low Carbon Contracts Company★4.4 (7)· London

The role uses Python (preferably PySpark), SQL, Azure (Data Factory, Synapse, Databricks, ADLS), and other cloud platforms. The team develops and maintains LCCC’s data warehouse, data pipelines, and governance artefacts to ensure reliable, integrated data for reporting.

Senior Data Engineer role at a private equity real estate firm, building cloud-based data pipelines and ETL processes using SQL, Python, Snowflake, AWS/GCP, and APIs. You'll integrate internal and external data sources, develop analytics solutions supporting investment decisions, and mentor two junior engineers while owning technical delivery.

Harvey Nash★3.8 (49)· London

SQL, Snowflake (or similar), AWS (S3, Lambda), Tableau/Power BI, and Python. You'll build and maintain data pipelines and integrations as a mid-level Data Engineer within a blended team at a global Media & Entertainment company.

You’ll build scalable data pipelines and engineering solutions using Python, SQL, AWS/Azure/GCP, Spark, Kafka, Airflow, and CI/CD for a technology consultancy delivering secure, data-driven analytics and intelligence projects.

Barclays★3.9 (6.9k)· London

The listing does not specify any concrete technologies, languages, or tools. You will join the Liquid Financing Technology team, building and enhancing data solutions for a modern cross-asset Client Risk platform used by Front Office, Risk, Finance, and Operations teams to monitor exposures, assess risk, and meet regulatory requirements.

Beamery★4.0 (1)· London

You will work with dbt, BigQuery, Kafka, PostgreSQL, MongoDB, Kubernetes, Python, and TypeScript/Node.js to build production ETL pipelines and an analytics layer. The data platform powers Beamery’s reporting and AI strategy, serving the company’s jobs, skills, and tasks data platform for talent lifecycle management.

Beamery★4.0 (1)· London

Architect Beamery’s data platform using dbt, BigQuery, Kafka, PostgreSQL, MongoDB, Typescript/Node.js, Kubernetes, Python, and Segment. The platform powers reporting and AI strategy for a skills and talent lifecycle management system. This is a senior individual contributor role setting long-term technical direction.

Transport for London★4.0 (429)· London

You'll use C#, Python, R, C++, Unity, R Shiny, Vissim, and Visum. This Network Performance team builds 3D simulations, dashboards, and data pipelines to communicate complex transport analytics for London initiatives like Superloop.

Pipedrive★4.2 (5)· London

You will lead marketing analytics at Pipedrive, a CRM software company, using Python or R, SQL, and dbt to build Marketing Mix Models, incrementality testing frameworks, and statistical models like LTV prediction and churn scoring. You will architect the marketing data layer and shape the long-term data stack roadmap.

You'll work with SQL, Databricks, Python, GA4, Google Tag Manager, and Salesforce. Building scalable marketing data pipelines and a centralized platform to connect CRM and marketing systems, enabling attribution and campaign measurement for a global company undergoing digital transformation.

You'll work with Python, LLM frameworks (LangChain, LangGraph), MLflow, and cloud ML platforms (GCP Vertex AI, AWS SageMaker) to build models and pipelines for Compare the Market's AI platform, powering insurance pricing, customer predictions, and personalisation.

Deloitte★3.9 (14k)· London

You will work with Azure (ADF, Synapse, Fabric, ADLS Gen2, Cosmos DB, AI Search), Python, SQL, and CI/CD/DevOps. You join Deloitte's Digital Innovation team to build end-to-end data pipelines and enable AI/GenAI use cases for Tax & Legal stakeholders.

Snowflake★3.7 (31)· London

Senior Solution Engineer at Snowflake supporting UK customers, using SQL (and ideally Python) to demonstrate Snowflake’s data cloud and AI capabilities. The role involves hands-on demos, proofs of concept, and collaborating with sales teams, partners, and product management to solve complex data challenges.

Snowflake★3.7 (31)· London

You'll work with Python, SQL, LangChain, Hugging Face, PyTorch, RAG, and modern data architectures (warehousing, lakes, lake house). As a Solution Engineer, you'll present Snowflake's AI Data Cloud, deliver demos and proof of concepts, and collaborate with sales and channel partners to drive adoption.

Snowflake★3.7 (31)· London

Work with Python, SQL, and modern AI/LLM ecosystems including RAG, LangChain, Hugging Face, and PyTorch, supporting data warehousing, data lakes, and lake house architectures. As a Solution Engineer at Snowflake, you drive sales cycles, deliver demos, and run enterprise Proofs of Concept for the AI Data Cloud.

Design optimisation engines using Gurobi, CPLEX, OR-Tools, Pyomo, and Python, deployed via CI/CD and cloud pipelines (Azure, AWS, GCP). The role focuses on large-scale scheduling, fleet optimisation, disruption management, and multi-constraint planning systems in a production environment.

You will use AWS, AWS Glue, Apache Airflow, Snowflake, Amazon QuickSight, SQL, and Python to build and maintain production ETL/ELT pipelines and cloud-native data platforms. You join a newly established Data Engineering team within a leading UK Financial Services organisation focused on unsecured lending.

You will work with Azure, Adverity, SQL, Python, cloud services (Azure, GCP, AWS), data orchestration tools (Airflow, Prefect), Git, and visualization tools (Power BI, Tableau, Datorama). As a data engineer in a media activation team, you will build and maintain ETL pipelines and reporting platforms to deliver marketing intelligence for clients.

You will work with GenAI tools like OpenAI, LangChain, Hugging Face, Vertex AI, and Bedrock, plus Python, PyTorch, TensorFlow, vector databases (FAISS, Pinecone), and cloud platforms. The Data Science Team builds and deploys LLM-based applications for enterprise use cases such as customer service, document automation, summarization, and knowledge retrieval.

The role uses SQL, R, and/or Python for advanced statistical modeling, machine learning, and psychometric analysis. It is part of the Talent Insights and Analytics function at EY, where you design and conduct organizational research to inform strategic talent decisions and workforce interventions.

The role involves Python, PySpark, SQL, and cloud platforms like Microsoft Fabric, Databricks or Snowflake, building data lakes, warehouses, and pipelines with Git-based version control. You'll join a Group IT team delivering data engineering and business intelligence solutions for a tier one main contractor in the construction industry.

Trainline★3.9 (17)· London

You'll build data pipelines using Spark, DBT, SQL, Python, Airflow, and Terraform on AWS data lakes with Iceberg, Jenkins, and GitHub Actions. You'll create data marts and models for Trainline, a rail-ticket booking platform, working with BI developers and data scientists on dashboards, analytics, and machine-learning datasets.

Expedia Group★3.8 (1.2k)· London

This Machine Learning Scientist II role develops and optimizes ranking models using machine learning and GenAI for travel lodging search and recommendations. The position involves Python, common ML frameworks, A/B testing, and deploying models into production. You will work on the Lodging Search Ranking AI team, collaborating with analytics, product, and engineering to improve traveler experiences.

You will use Python, pandas, scikit-learn, PyTorch, and Hugging Face to wrangle messy legacy data and build production-ready AI models. The team is building an AI operating system for industries with fragmented, complex data, shipping models for forecasting, optimisation, and recommendation.

Use Python (pandas, NumPy, SciPy, matplotlib/seaborn) and SQL with cloud-based data tools and large language models. Build predictive and statistical models to identify alpha signals from alternative data for a leading investment manager with a global presence.