Work with Microsoft Fabric (Lakehouses, Warehouses, Dataflows, Pipelines), Azure (SQL, Data Lake, Data Factory), SQL, Python, and REST API/SFTP to build ETL/ELT solutions. You will deliver modern data integration solutions for a diverse portfolio of clients within RSM’s Global VAT Team.

You will work with AWS, dbt, Spark, SQL, Kafka, Flink, and Airflow on a modern event-driven lakehouse using medallion architecture. The team builds and evolves the next-generation data platform for FDJ UNITED’s Sportsbook product, powering analytics, trading insight, and machine learning across multiple brands and markets.

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.

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.

FDJ UNITED★4.0 (96)· London

Build and maintain batch and streaming data pipelines on AWS using dbt, Spark, SQL, Kafka/Flink, and Airflow. Work on the Sportsbook Data Platform, a modern event-driven lakehouse transforming sportsbook data (bets, offers, etc.) into curated datasets for analytics, trading insight, and machine learning.

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.

Work with SQL, Python, and modern data technologies (dbt, Spark, containers, DevOps tooling, orchestration tools, Git, AI/ML). As a Solution Engineer for the UK market, you present Snowflake’s technology and vision, working hands-on with prospects to demonstrate value through demos, proof-of-concepts, and design.

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.

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).

Snowflake★3.7 (31)· London

Work hands-on with SQL and Python, using modern data tools such as dbt, Spark, containers, DevOps tooling, orchestration tools, and Git. Present Snowflake’s cloud data platform technology and vision to executives and technical contributors, demonstrating value through demos, proofs of concept, and implementations. Partner with account sales teams and channel partners to help customers evaluate and adopt Snowflake.

Snowflake★3.7 (31)· London

This role uses SQL and Python, with experience in modern data technologies such as dbt, Spark, containers, DevOps tooling, orchestration tools, and Git. You will work with the account sales team and channel partners to present Snowflake’s data platform and vision, solving complex data challenges for customers in the UK market.

Snowflake★3.7 (31)· London

You'll work with SQL, Python, and modern data tools (dbt, Spark, containers, DevOps, Git) as a Solution Engineer, partnering with sales and channel teams to help customers adopt Snowflake's cloud data platform for analytics, data engineering, and AI/ML.

Snowflake★3.7 (31)· London

Work with SQL, Python, and modern data technologies (dbt, Spark, containers, DevOps, orchestration tools, Git) to demonstrate Snowflake’s data cloud platform. You partner with account sales teams and channel partners to solve complex data challenges for UK travel customers.

Lead a data team using SQL, Databricks, Azure, Spark, and LLMs to build scalable pipelines, ETL workflows, and a Data Lake for Sharegain’s securities lending platform. The team also

Insulet Corporation★3.1 (189)· London

Work with SQL, Python, DAX, Spark, Microsoft Fabric, Databricks, CRM, ERP, AWS, and Salesforce to integrate datasets and build reporting solutions. As the Customer Care Data Lead, you will own data governance, definitions, metric logic, and quality standards for Insulet’s International Customer Care organization, which supports the company’s Omnipod diabetes product platform.

Design, build, and deploy GenAI and ML solutions using OpenAI APIs, RAG, Python, Databricks, Spark, Delta Lake, and AWS (S3, Redshift, Lambda). You will work on predictive models and enterprise GenAI apps for Product, Sales, Finance, Marketing, Customer Success, and Engineering, owning projects end-to-end and integrating with Salesforce and Oracle platforms.

Prima★3.6 (45)· London

You'll work with Kafka, Flink, Spark, Databricks, Python, AWS, Redshift, PostgreSQL, and DevOps/CI-CD tools to build data products and pipelines for Prima's pricing and underwriting domain. The role bridges machine learning and engineering, focusing on data architecture, transformation, governance, and enabling teams to ingest, store, and serve data products. You'll join over 350 engineers across Prima, an online motor insurance provider trusted by 5 million drivers expanding in the UK and Spain.

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

Lead the development and operation of a large-scale AWS data platform using Redshift, S3, Glue, Lambda, Athena, EC2, Kinesis, Python, SQL, Bash, Spark, CI/CD, and DataOps. Provide senior technical leadership, mentor engineers, and oversee batch and streaming data pipelines for a major organisation.

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 build data pipelines using Python, SQL, and Spark, processing structured and unstructured data for analytics, machine learning, and AI workflows on a collaborative engineering team.

Design and build production-grade ML systems using MCP servers, recommendation systems, RAG pipelines, LLMs, and foundation models with Python, TensorFlow, PyTorch, FastAPI, and LangChain. You will own the end-to-end AI lifecycle for a sales data platform, deploying models into batch/real-time environments to drive forecasting, segmentation, and early warning systems. This role focuses on embedding context-aware intelligence into decision-making tools for business stakeholders.