Principal Data Engineer role using GCP, Python, Node.js, BigQuery SQL, and Jenkins CI/CD. The team enables Sky’s growth through Data and AI, deepening customer relationships, optimising commercial performance, and enhancing operational efficiency. The role provides technical leadership, managing Solution Architects and setting engineering standards.

MAREX★3.2 (6)· London

Risk Data Analyst at Marex works with the Data Platform, Power BI, and structured/unstructured datasets. The role bridges Risk and Technology, supporting data-led risk management, monitoring, and reporting across disciplines like market, credit, and operational risk.

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.

Work with Microsoft Fabric, Databricks, Azure, Snowflake, Python, Spark, SQL/NoSQL, PowerShell, Azure Data Factory and Azure DevOps to build a Fabric Data Lakehouse for USS’s Investment Management business, implementing scalable ETL/ELT frameworks across a medallion architecture. Share knowledge across a small team of data engineers and collaborate with architects, business stakeholders and data teams.

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.

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.

HCLTech★3.7 (11k)· London

Work with Quantexa Decision Intelligence Platform, Spark/PySpark, Python/Scala, and Big Data (Hive/HDFS) to design and develop data ingestion, transformation, and ETL pipelines. Focus on entity resolution, network analytics, and graph-based data models for analytics use cases.

Work with Microsoft Azure Data Platform, Microsoft Fabric, PySpark, SQL (T-SQL and Spark SQL), Python, Azure DevOps, and Power BI. You will build enterprise-scale data pipelines and support Data Lakehouse and Data Warehouse solutions for SmartestEnergy, a global energy company.

Design and develop solutions on the Quantexa Decision Intelligence Platform, building data ingestion and ETL pipelines with Spark/PySpark, and using Python/Scala. The role involves entity resolution, network analytics, graph-based data models, and integrating structured/unstructured data, working with the Big Data ecosystem (Hive/HDFS).

Build and own the machine learning models (propensity, uplift, contact strategy) that decide who, when, how often, and on which channel (voice, WhatsApp, email, SMS) Murphy's AI agents contact debtors to maximize recovery within legal limits. Work in Python, TypeScript, AWS, and PostgreSQL; design, run, and ship A/B tests and bandits on live traffic.

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.

Bloomberg★3.8 (1.1k)· London

You'll work with Python, SQL, and modern AI-assisted tools to own the data management strategy and roadmap for Bloomberg's environmental regulatory data products, including EU Taxonomy, SFDR, and CSRD. You'll partner with Engineering and Product to evolve data models, quality frameworks, and operational controls that ensure scalable, auditable data products.

Mastercard★4.0 (846)· London

You will work with LLMs, GenAI, Agentic AI, PowerBI, Qlik Sense, Tableau, AWS, Databricks, and Microsoft Azure, with Python and SQL preferred. Within Vocalink’s Data & Insights function, you will deliver data-led and AI-driven solutions for UK payment reporting and customized analytics.

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.

Design, build, and deploy quantitative models using Python, R, and libraries (numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot) plus NLP tools, SQL, AWS, Sagemaker, DataBricks, Snowflake, MLFlow, and Weights & Biases. The team creates systematic country risk analytics and ML/NLP pipelines for BMI’s market insights, supporting clients in risk assessment.

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

Hays★3.5 (1.4k)· London

You will work with Snowflake, AWS, Python, SQL, dbt, Airflow and GitLab CI/CD. The role is part of a major cloud transformation programme building a next-generation, cloud-native data platform, including ETL/ELT pipelines and migrating legacy environments.

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.

You will work with Snowflake, Azure Data Factory (ADF), and dbt Cloud to build scalable ELT pipelines. You’ll design and improve modern data solutions on the Retail Analytics Data Hub, serving protection, retirement, annuities, and pensions domains. As a hands-on lead, you will also mentor other data engineers.

WGSN★4.0 (21)· London

Drive global interiors forecasting strategy using AI, data analytics and emerging technologies. Define and direct WGSN's thought leadership and content portfolio for home, interiors and hospitality across short-, medium- and long-term horizons.

Fitch Solutions★3.0 (2)· London

As a Data Scientist at BMI (a Fitch Solutions business), you will design, build, and deploy quantitative models using Python and R (e.g., numpy, pandas, scikit, pytorch) to power advanced analytics. You will develop and maintain ML/NLP and data pipelines, working with Economists and Analysts to build risk models and generate insights from structured and unstructured data.

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 will work with Microsoft Power BI (including composite models over Azure Analysis Services), Snowflake, Power Automate, and SQL. You will build and maintain the reporting estate supporting INEOS Automotive's global sales, retailer, and customer experience operations.

You will work with Snowflake, ADF, and dbt Cloud to design and build scalable data pipelines and modern data solutions across the Retail Analytics Data Hub. The team handles data domains for protection, retirement, annuities and pensions, using Kimball-style dimensional modelling and ELT approaches. This is a hands-on technical leadership role that involves mentoring and coaching data engineers on the Retail DataOps team.

**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.