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.

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.

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.

Bloomberg★3.8 (1.1k)· London

This senior full-stack role involves building Bloomberg’s DataHub platform using React for the UI and Java, Kotlin, Scala, or Go for backend services. You will design control-plane systems enabling engineers to discover, query, publish, and manage datasets at scale, while also building the semantic foundation for AI-assisted data workflows.

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.

Wise★3.5 (42)· London

You will use Python, dbt, Airflow, Kafka, Trino/Iceberg to architect high-volume streaming and batch data pipelines. As the data lead on the Marketing Platform team within Scalable Growth, you own the data infrastructure and vendor integrations (Meta, Google) that power Wise’s global customer acquisition engine.

Wise★3.5 (42)· London

Work with Trino, Iceberg, Kafka, dbt, Airflow, Python, SQL and Java/Scala to build streaming data pipelines on a Lakehouse using Medallion Architecture (Bronze/Silver/Gold). You will own data extraction, cleaning and modeling for the Data Onboarding team, which bridges product events and audit-ready financial structures for Wise’s global cross-border money movement platform.

IQVIA★3.7 (2.7k)· London

Works with cloud-native architecture, data warehousing, AWS, and big data technologies including Hive, Spark, Presto, Cassandra, Hadoop, and ML

You will work with MongoDB, Postgres, Kinesis, Flink, Spark, ElasticSearch, Redis, Trino, Presto, Snowflake, Kubernetes, and public cloud. The Platform Engineering team designs and develops core data storage, streaming, caching, and indexing platforms that power Scale AI’s products for LLMs and generative models.

Tripledot Studios★2.8 (4)· London

Senior Machine Learning Engineer will work with ML techniques, CI/CD, Docker, Kubernetes, SQL, Python, MLFlow, Kubeflow, Trino, and AirFlow. The AI group implements ML algorithms for personalization across mobile game studios, directly improving retention, revenue, and player experience.

Universal Music Group★4.0 (408)· London

Senior Java Developer working with Spring Boot, relational databases, SQL, AWS, Docker, and Kubernetes on a greenfield platform serving UMG staff globally. The role involves web application and API development, integrating with internal systems, and leading teams on feature delivery and technical direction within Universal Music Group's enterprise software development.

CrowdStrike★3.8 (54)· London

You'll lead a newly forming Data Replay & Recovery Team within CrowdStrike's Data Platform organization, working with Java/Scala, Python, Apache Hadoop ecosystem technologies (Spark, Kafka, Flink, Iceberg/Delta Lake, Presto/Trino), SQL/NoSQL databases, Docker, and Kubernetes to build self-service data replay applications for a security data lake processing petabytes of data daily. The role requires 3+ years of hands-on engineering management experience and 7+ years combined backend/cloud and data platform engineering expertise.

G-Research★3.6 (18)· London

You'll design and operate large-scale distributed analytics platforms using Spark, Trino, Kafka, ClickHouse and Airflow across on-premises and AWS environments, with infrastructure-as-code (Terraform/Ansible), Linux, Python, and CI/CD tools like Jenkins and ArgoCD. G-Research applies scientific methods to quantitative finance research and trading, and you'll collaborate with research and engineering teams to build highly available, scalable analytics services that accelerate discovery across the firm.

Citi★3.9 (21k)· London

You will build trading analytics and desk tooling using Python (Pandas, FastAPI, Airflow, Streamlit), high-performance data stores (Trino, Snowflake), and agentic AI frameworks for Citi's Equities Technology team supporting Derivatives Flow, Delta 1, and Exotics desks. The role involves creating real-time pricing, risk analytics, backtesting frameworks, and data pipelines for traders and quants across execution, prime clearing, and post-trade platforms during a multi-year technology transformation.

Tripledot Studios★2.8 (4)· London

You'll build and maintain scalable AI/ML infrastructure using Kubernetes, Terraform, AWS, GCP, and tools like Airflow, Spark, and Kubeflow to support model training and deployment across Tripledot Studios' mobile gaming operations. Reporting to the IT team within a 2,500+ person global games company, you'll bridge technical solutions and live game engines while partnering with central AI, data, and studio teams to expand their data/ML platform and support productivity initiatives.

JPMorgan★3.9 (20k)· London

You'll work with Python, PySpark, dbt, SQL, Apache Airflow, Kafka, Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure) to design and operate cloud-native data pipelines and lakehouse platforms powering analytics and regulatory reporting for JPMorgan's Personal Investing division. The role involves mentoring junior engineers, establishing technical standards, and translating business requirements into scalable, production-grade data solutions serving hundreds of thousands of UK investors.