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.

You'll design and own end-to-end RAG pipelines for payments domain content using Python, Azure Data Factory, Functions, ADLS, CosmosDB, and AI Search, with CI/CD via GitHub Actions and Azure DevOps. RedCompass Labs builds AI-powered payment transformation and financial crime detection solutions, including the RedFlag Accelerator for identifying human trafficking. You'll collaborate with AI engineers and payments experts to turn regulatory documents and handbooks into a reliable retrieval layer for their proprietary multi-agent AI platform.

You will work with C++, Python, Linux, machine-learning libraries, Google Cloud, Airflow, InfluxDB, and Grafana. This role builds data engineering and prediction tools for systematic equity trading, developing software for quantitative research, maintaining data pipelines, and implementing large-scale computation and serialization frameworks.

You will work with AWS, Kubernetes, Terraform, Python, Java or Scala, and AI-driven development tools (Claude, LLMs). You will build and maintain the distributed-compute and data-science platform that powers Macquarie's trading and analytics workflows, collaborating with quantitative analysts and trading desks.

Use Python, Azure, Docker, Kubernetes, Apache Airflow, and GitHub Actions to build scalable ETL pipelines, financial data pipelines, and cloud-native infrastructure. This front-office role is at a systematic equity hedge fund modernising its quantitative research platform, working directly with portfolio managers and researchers. Experience with S&P Xpressfeed, Snowflake, Bloomberg, MSCI Barra, Databricks, and LLMs is advantageous.

Rebuild data infrastructure for a market-neutral systematic equities fund using Python, Microsoft Azure, Docker, Azure Kubernetes, Apache Airflow, and GitHub Actions for CI/CD. Work on ETL pipelines, vendor integration, and cloud-based research platforms, with relevant experience in Snowflake, Bloomberg, MSCI Barra, or Databricks. The role spans data engineering and quantitative development to transform financial data into investment signals.

Build and maintain scalable data pipelines (BigQuery, Cloud Composer, Airflow, Dataflow, Spark, Flink, dbt) on GCP for AI/ML experiences. Use Docker/k8s, Terraform, SQL, shell scripting, and monitoring tools (Monte Carlo, Looker, NewRelic, Splunk). Collaborate with product engineering, data science, and business teams.

The Specialist Works★4.8 (5)· London

You will primarily work with Python, SQL, Azure, and the Adverity platform to create, monitor, and optimize data pipelines. You will be a key member of a dynamic media activation team, delivering bespoke marketing intelligence reports and ETL solutions for the agency's clients.

Cboe Global Markets★3.7 (14)· London

You'll work primarily with Python to design and build highly reliable trading systems, working closely with advanced SQL, Linux, and optionally PostgreSQL, Snowflake, Apache Kafka, Apache Airflow, Django, Flask, or FastAPI. You'll expand data pipeline and event streaming functionality for Europe's largest equities exchange and related platforms, while leading complex projects, mentoring developers across multiple global teams, and participating in production support for Cboe Europe's trading operations.

You will use Python, dbt, Airflow, Kafka, and Trino/Iceberg to architect scalable data pipelines and streaming architectures. As the embedded data lead on the Marketing Platform team, you’ll build and maintain the data infrastructure and third-party integrations (e.g., Meta, Google) that power Wise’s global customer acquisition engine.

SQL, MySQL, PostgreSQL, Doris Event, QuickSight, and possibly Amplitude, Mixpanel, GA4, Airbridge, Adjust, Airflow, dbt, Git or Python. You will own analytics schema, data models, and BI dashboards for ZYMIX, a Gen Z social super-app launching in the UK, bridging product analytics with data building.

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.

LiveScore Group★3.4 (14)· London

You will build and deploy robust data pipelines using GCP services (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Bigtable, Spanner, Airflow, Terraform) and Python or SQL. As part of LiveScore Group's Data Team, you will develop scalable data systems for real-time AI/ML workloads that power sports media and betting for brands LiveScore, LiveScore Bet and Virgin Bet.

LiveScore Group★3.4 (14)· London

Use GCP (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Bigtable, Spanner, Firestore), SQL, Python, Terraform, Airflow, Docker and AI tooling. You will lead the data team in designing scalable pipelines, data models and real-time systems that power sports media and betting brands.

You will work with Python, dbt, Airflow, Kafka, Trino/Iceberg, and Martech tools like Braze. As the data lead on the Marketing Platform team within Scalable Growth, you will build and scale high-volume streaming and batch data pipelines to power Wise’s global customer acquisition. You will also coach software engineers in data best practices.

You'll work with Trino, Iceberg, dbt, Airflow, Kafka, Python, SQL, Java or Scala to build and optimize data pipelines on a Lakehouse following Medallion Architecture (Bronze, Silver, Gold layers). You'll join Wise’s Data Onboarding Team, part of the Finance Squad that stewards the company’s financial truth by processing hundreds of millions of high-throughput financial events daily into audit-ready structures. The team abstracts product complexity into reusable, domain-agnostic stream-enrichment pipelines.

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.

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 work with GCP services (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Bigtable, Spanner, Firestore, Cloud Composer, Vertex AI), SQL, Python, Terraform, Airflow, and Docker. The data team builds scalable, real-time data pipelines and AI/ML workloads to power sports media and betting products for LiveScore, LiveScore Bet, and Virgin Bet. You will lead architectural decisions, own data-solution design, and mentor engineers.

You will work with GCP services (BigQuery, Dataflow, Pub/Sub, Cloud Storage, Bigtable, Spanner, Firestore), Cloud Composer, Airflow, Docker, Terraform, Python, and SQL. The team builds scalable data pipelines and models to power real-time AI/ML workloads for LiveScore’s sports media and betting brands.

Senior Software Engineer II building data pipelines on Trino, Iceberg, Kafka, dbt, Airflow, and Python/SQL for a Finance Squad. The team handles high-throughput financial event data within a Medallion Architecture, creating reusable stream-enrichment pipelines to support financial reporting and assurance at a global money-transfer company.

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.

Build and maintain the foundational platform infrastructure at Astronomer, using Go, Kubernetes, and distributed systems design across AWS, GCP, and Azure. The team owns the multi-cloud platform behind Astro, Observe, and the IDE, focusing on scalability, operational maturity, and system reliability for enterprise customers.

Python, SQL, Spark, Airflow, and AWS are used to build and maintain data pipelines, including ELT/ETL, for the Search and AI Platform powering Scopus, ScienceDirect, and AI-driven research solutions. AI-assisted tools like Claude Code, Copilot, or Codex are part of the workflow.

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.