Cint★3.5 (13)· London

Use Python and SQL for statistical modeling and machine learning to optimize Cint's programmatic research marketplace (Cint Exchange). You will analyze marketplace dynamics, conduct A/B tests, and build predictive models to guide product and pricing strategy.

Design, build and optimise ETL data pipelines using Databricks, PySpark, Python, and SQL for a leading global investment bank. You will work on large-scale enterprise data platforms in a fast-paced financial services environment.

Working with Core Python, Pandas, NumPy, Flask/FastAPI/Django, SQL, and Unix/Linux, you will build backend applications and data processing pipelines for trading and risk management within an investment banking environment, supporting risk calculations, trade workflows, and reporting.

SmartestEnergy★4.1 (15)· London

You will work with Microsoft Azure Data Platform, Microsoft Fabric, PySpark, SQL, Python, Azure DevOps, CI/CD, and Power BI to build enterprise-scale data pipelines and Data Lakehouse/Data Warehouse solutions. The team develops modern cloud-based data solutions supporting ETL/ELT processes across Medallion Architecture for SmartestEnergy’s energy digitisation and decarbonisation goals.

bp★3.8 (5.2k)· London

Work hands-on with Python, SQL, C#, Spark/PySpark, Palantir Foundry, planlogic EOS ETRM, Stonebranch, and AWS to build and maintain backend services, RESTful APIs, front-end components, and data pipelines. You will support bp’s LNG Energy Trading and Risk Management applications, including bespoke solutions for trade capture, operations, analytics, risk, reporting, and finance. This Staff Engineer role also includes mentoring and line management of the engineering team.

You will lead Azure Databricks architecture, designing enterprise Lakehouse solutions with Apache Spark, PySpark, Delta Lake, Azure Data Factory, Data Lake Gen2, Event Hubs, Synapse, Python, SQL, Terraform, and CI/CD. This is part of a major Energy & Utilities transformation programme, specifically supporting critical Energy Trading data.

Bloomberg★3.8 (1.1k)· London

You will work with Python, SQL, PySpark, Pandas, NumPy, Airflow, dbt, Kafka, Iceberg, Trino, Superset, and data visualization tools. The Entity Data team manages core entity data for over 7 million public and private companies, supporting reference data and private markets; as Data Quality Manager you define and execute the quality strategy.

McKesson★3.5 (7.7k)· London

Senior Data Engineer: Snowflake, dbt, Airflow, ADF, Python, Databricks, Azure, AKS, Infrastructure as Code, CI/CD. You will own and build the ClarusONE data platform, designing scalable pipelines and establishing engineering standards for reliability, security, and compliance.

Senior Data Engineer role owning the ClarusONE data platform, building pipelines with Snowflake, dbt, Airflow, ADF, Python, and managing IaC on Azure/AKS. You will establish engineering standards, ensure data lineage and governance (SOX), and collaborate with Analytics, Data Science, and Software Engineering teams.

Senior Python Developer role building trading and risk platforms using Python, SQL, Pandas, NumPy, Flask/FastAPI/Django, PySpark, Unix/Linux shell scripting, and enterprise platforms like Quartz or SecDB. The team develops backend services, data pipelines, and risk applications for trade lifecycle, risk calculations, and regulatory reporting within investment banking.

Work with Microsoft Fabric, Azure, SQL and PySpark on building modern data platforms and scalable ETL/ELT pipelines. The role is part of a large organisation undergoing a significant data transformation, developing data products and integrating source systems.

You will use SQL, Python, Spark/PySpark, Pandas, orchestration tools, AWS/Azure platforms (Databricks, Redshift, Microsoft

Use Python, C#, .NET, TypeScript, React, Angular, SQL, PySpark, and agentic development tools (e.g., GitHub Copilot). You will be a Software Engineer III on the LNIP intelligence core platform, developing a semantic search API and maintaining an internal data curation tool.

You will use Python/PySpark, AWS S3/Glue/EMR, SageMaker, SQL, Git, CI/CD, Terraform/CDK, and Airflow/dbt/Step Functions to migrate ML data pipelines from Databricks (Spark/Delta Lake) to an AWS SageMaker MLOps platform. You join a small Databricks workstream team building and migrating feature engineering, feature store, and data access layers for production pipelines in a regulated iGaming environment.

WNS, a Business Process Management company, seeks a Lead Data Engineer with 10+ years experience to develop features and drive architectural decisions on their cloud delta lakehouse platform using SQL Server, SSIS, T-SQL, Azure Data Factory, ADLS, Azure SQL Database, PySpark, Spark SQL, Databricks, and Delta Lake. The role involves mentoring junior engineers, establishing engineering standards, and leading complex data warehouse initiatives within an agile team in central London.

You will work with Python/PySpark, Databricks, AWS SageMaker, S3, Glue, Lake Formation, IAM, Terraform/CloudFormation/CDK, and Git/CI/CD. As part of a small delivery team, you will migrate ML data pipelines from Databricks to a SageMaker-based MLOps platform for a regulated iGaming client, building production pipelines and proving parity between platforms.

Design, build and evolve modern data infrastructure using Python, PySpark and SQL, with Snowflake or Databricks on AWS, plus orchestration tools and CI/CD. Your work powers SaaS solutions that help financial institutions solve operational and compliance challenges.

Allianz★3.8 (3.4k)· London

You will work with Docker, Kubernetes, Terraform, Azure, Azure DevOps, Python, SQL, PySpark, dbt, Microsoft Fabric, and SQLMesh. Joining a small stream-aligned agile team at an insurance company, you will build and maintain production-ready data and ML systems, including real-time API endpoints serving 10+ million daily requests.

The Senior Data Engineer (ML) works with Python, PySpark, AWS data and ML stack (S3, Glue, IAM), SageMaker, SQL, Git, CI/CD, and Terraform/CloudFormation/CDK. They are part of a team migrating an ML estate from Databricks (Spark/Delta Lake) to an AWS SageMaker-based MLOps platform for a regulated iGaming environment, building and migrating production data pipelines that feed model training and inference and implementing parity testing.

Work with Databricks, Azure, Python/PySpark, Git, CI/CD, and AI coding tools (GitHub Copilot, Cursor, Claude Code) to build and scale data pipelines for an investment management firm. You will design governance, monitoring, and security frameworks for a cloud data lakehouse while optimizing performance and producing production workloads. This is a key hire on a small, high-impact team.

Migrate ML data pipelines from Databricks (Spark/Delta Lake) to an AWS Sage

You will work with Azure Databricks, PySpark, Python, SQL, Delta Lake, Structured Streaming and CI/CD tooling on a multi-year programme migrating Oracle data platforms to a cloud-native platform. The project supports Endur, global reporting, analytics and risk management for a leading global energy trading organisation while reducing latency to near real-time.

You will work with Python, PySpark, SQL, and Azure Databricks to build predictive models and scalable analytics pipelines. This is a contract role on a digital transformation programme focused on developing innovative products on a large-scale UK healthcare data platform for population health management.

McKinsey & Company★4.2 (952)· London

You will work with AWS (S3, Lambda, Glue, Snowflake), Python, SQL, Tableau, Git, Databricks, and PySpark. As part of McKinsey’s Transformatics team, you will build cloud-based data platforms and ingestion pipelines to power analytics and machine learning for the Wave SaaS product. You will collaborate with a geographically distributed team of data engineers, data scientists, and project managers.

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.