Design, develop, and optimize scalable data solutions using Snowflake, GitHub, and Octopus Deploy, with CI/CD pipelines and cloud platforms (Azure, AWS, GCP). This role leads the design, implementation, and deployment of modern cloud-based data platforms, including ELT/ETL pipelines and secure automated deployments.

Imperial College London★4.2 (238)· London

You will work with R, Python, Stata, or SAS, plus SQL and cloud-based or high-performance computing. The role uses large-scale real-world datasets to investigate metabolic dysfunction in type 1 diabetes and develop clinical risk prediction models. You join the multidisciplinary Misra Group within Imperial’s Department of Metabolism, Digestion and Reproduction.

EPAM Systems★3.8 (703)· London

You will lead the design and optimization of scalable cloud-native data architectures using Azure Databricks, PySpark, Delta Lake, and Azure services, while implementing CI/CD with Terraform, GitHub Actions, or Jenkins. The role involves driving data strategies, mentoring engineers, and enabling AI-driven solutions with Databricks ML/MosaicML.

SSE PLC★3.1 (539)· London

Work with SQL, Python, Databricks and Power BI to build statistical and machine learning models. You will apply analytics and AI to assess risk, controls and assurance activities for SSE, an energy company investing in electricity infrastructure.

You will work with Generative AI, LLMs, OpenAI, LangChain, Hugging Face, PyTorch, TensorFlow, FastAPI, Streamlit, and cloud platforms (AWS/GCP/Azure). You will design and deploy GenAI solutions—including RAG pipelines, fine-tuning, and prompt engineering—for enterprise use cases such as customer service, document automation, and knowledge retrieval on the Data Science Team at a global data and AI company.

A Core AI Engineer at LSEG designs, develops, and deploys enterprise-grade AI products and services, building agentic workflows, RAG solutions, and scalable integrations with LLMs and vector databases. The role leads technical implementation across AI initiatives, mentoring engineers and defining solution architecture. The team is transforming how LSEG operates by using AI to improve service resilience, automate workflows, and accelerate engineering productivity.

Wise seeks a Senior Data Engineer to join the Scalable Growth team. You will work with Python, dbt, Airflow, Kafka, and Trino/Iceberg to build and maintain data pipelines, a Customer Data Platform, and marketing infrastructure. The role involves bridging engineering and analytics while coaching other engineers.

Work with AWS, Python, Kafka, Kubernetes, gRPC, Docker, Terraform, CloudFormation, and CI/CD tools (Jenkins, GitHub Actions, CircleCI). You will design, build, and scale the data pipelines and cloud infrastructure powering AeroVect's autonomous driving platform, owning systems from the ground up.

The role involves Python, pandas, OOP, SQL (PostgreSQL, Snowflake), CI/CD pipelines, git/GitHub, and GitHub Copilot, with JavaScript, Flask, or FastAPI helpful. You'll develop in-house fund management tools for the Index team at L&G Asset Management, analyzing portfolio performance and supporting data pipelines. L&G is a major global asset manager and UK financial services group.

Millennium Management★3.8 (21)· London

Python, Linux, SLURM, Kafka, Solace, Pulsar, Memcache, Redis, AI RAG/MCP agents, Datadog, ELK, SQL, NoSQL, Kdb. You will build real-time portfolio management and intraday analytics platforms for Millennium’s front-office EQRT Services team, supporting strategy research, backtests, and risk/factor analytics.

You’ll build and maintain scalable data pipelines and implement observability, monitoring, and data quality checks using Python, SQL, shell scripting, containerization, and IaC tools (with Scala/Java preferred). You’ll support AI/ML-driven financial technology platforms at a global fintech company, collaborating with product engineering, data science, and business teams.

You will work with Databricks, Azure SQL, Azure Data Factory, Python or PySpark, and advanced SQL to build and maintain ETL/ELT pipelines. The role supports a large-scale data platform migration project moving workloads from Azure SQL to Databricks as part of an established data team.

You will work hands-on with Azure, Databricks, and SQL, building scalable ELT pipelines and Lakehouse architectures. You will operate as a senior individual contributor on a major enterprise data platform transformation for a global mining company.

You'll work with Python, SQL, Azure or AWS, Databricks/Snowflake/Redshift, Airflow/Azure Data Factory/Prefect, and dbt/Kafka/Terraform. The role builds and optimises cloud-based data infrastructure supporting analytics, reporting, and future AI initiatives for a fast-growing technology company.

Python, SQL, Apache Spark, Airflow, Azure Data Factory, Docker, and Kubernetes. You will design, build, and maintain data-driven applications, integrating with data lakes, lakehouse architectures, and enterprise databases for large-scale analytics systems.

You'll work with Python, SQL, ETL/ELT, FastAPI, and AI/LLMs to build a mission‑critical Data Migration Platform that connects to legacy CRMs and onboard financial agencies at scale.

Write Python and FastAPI to build a real-time intelligence platform for private markets, used by venture capital and private equity firms to analyze live data and make faster investment decisions.

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.

Wise★3.5 (42)· London

Work with Python, dbt, Airflow, Kafka, Trino, and Iceberg to build high-volume streaming and batch data pipelines. You'll join the Marketing Platform team to drive data architecture for Wise’s global customer-acquisition engine, bridging platform and analytics engineering.

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.