Work with Python, FastAPI, Docker, DuckDB, JSON Schema and Git to design, build and ship client ETL pipelines that map raw bank data onto the FIRE regulatory reporting standard. You will maintain a shared ETL framework, write validated mapping code, and mentor junior engineers at Suade, a regtech SaaS company automating compliance for financial institutions.

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.

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.

Work with Python, BeautifulSoup, Selenium, and Apify to scrape dynamic web content, extract data from complex structures, and deliver structured datasets. You will join the Tendem project, driving specialized data scraping workflows for real-world applications. LLM and AI frameworks are also used to enhance automation.

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.

FDM Group★2.9 (270)· London

You'll work with Python, pandas, JSON, REST APIs, LLMs, RAG, vector embeddings, and semantic search to build data ingestion pipelines and scalable platforms that enable AI-powered analytics and decision support within a leading global investment bank.

The Head of AI works with Python, NLP pipelines, LLMs, knowledge graphs, and clinical ontologies like SNOMED CT and ICD. This role leads a team building Dyad's Semantic AI platform combining structured knowledge with generative AI to improve healthcare delivery, with products such as BetterLetter for clinical correspondence processing. The position designs and operationalises the graph-integrated generative architecture for production systems handling unstructured clinical text, including evaluation and compliance frameworks.

Cushman & Wakefield★3.6 (2.3k)· London

Senior Data Engineer role using Databricks, Python, PySpark, SQL, Azure, and Unity Catalog. You will build an AI-amplified data platform for a global real estate services firm, shifting the team from writing code to orchestrating AI. Hands-on role with influence on technical direction.

FDM Group★2.9 (270)· London

Python, pandas, JSON, REST APIs, FastAPI, LLMs, RAG, vector embeddings, semantic search, Plotly, and Plotly Dash. You will build scalable data platforms and AI-powered solutions for a leading global investment bank, enabling intelligent scenario modelling and decision support.

Work with Python, SQL, relational databases, APIs (RESTful, JSON), and data pipelines. As a Data Engineering Intern at Crebain AI, you will maintain and optimize databases, integrate APIs, and design data pipelines to support the company's data infrastructure.

WTW★3.6 (1.7k)· London

The Data Engineer will work with Microsoft Fabric, Azure Synapse, Azure Data Factory, PySpark, Python, Power Automate, and Copilot/AI tools to design, build, and optimize data pipelines. They will integrate AI/LLM models and Power Platform automation into data workflows, collaborating with data experts and business teams.

Red Badger★0.0· London

Databricks Engineer role in Red Badger's Data & AI practice. You'll work with Databricks, AWS (RDS, DynamoDB, S3, Glue, EMR, Athena, SageMaker), Azure, SQL, Python, PySpark, and dbt. You'll lead a team of data engineers to build client-facing data solutions using Medallion Architecture.

LSEG★3.7 (402)· London

FTSE Russell seeks a Quantitative Engineer to build scalable applications supporting index calculations, back-testing, and analytics using Python, SQL, numpy, pandas, scipy, and cloud-native solutions with RESTful APIs and CI/CD pipelines. The role combines software engineering with quantitative finance to develop tools for index monitoring, validation, and rebalancing across equity, fixed-income, currencies, and commodities. Requires 2+ years in quantitative analytics within financial services and an advanced degree in Mathematics, Computer Science, Financial Engineering, Statistics, or Physics.

You'll build data platform services and tools using Python, Java, or C# alongside distributed systems technologies like Kafka, Cassandra, and Kubernetes to help traders, researchers, and back-office staff discover and share data across DRW, a diversified trading firm. You'll design architectural patterns, mentor engineers, and own solutions end-to-end while collaborating across the organization in a fast-paced trading environment.