You'll work with Python (Pandas, Arrow, Spark) and potentially Lakehouse tools (Delta Lake, Databricks, AWS). Joining Global Data Engineering, you provide first-line support for a high-frequency trading market maker, ensuring robust data pipelines and APIs for trading teams.

You will lead Azure Databricks architecture, designing enterprise Lakehouse solutions with Apache Spark, PySpark, Delta Lake, Azure Data Factory, Data Lake Gen2, Event Hubs, Synapse, Python, SQL, Terraform, and CI/CD. This is part of a major Energy & Utilities transformation programme, specifically supporting critical Energy Trading data.

Work with Azure OpenAI, AI Foundry, Databricks Mosaic AI, MLflow, Genie, AgentBricks, LangChain, LangGraph, AutoGen, Delta Lake, DLT, Unity Catalog, Python and SQL. You will design, build and deploy GenAI, RAG and Agentic AI solutions from prototype to production as part of a major AI and data transformation programme across a global energy organisation’s trading business.

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.

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.

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.

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.

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.

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 use Python/PySpark, AWS S3/Glue/EMR, SageMaker, SQL, Git, CI/CD, Terraform/CDK, and Airflow/dbt/Step Functions to migrate ML data pipelines from Databricks (Spark/Delta Lake) to an AWS SageMaker MLOps platform. You join a small Databricks workstream team building and migrating feature engineering, feature store, and data access layers for production pipelines in a regulated iGaming environment.

Microsoft★4.2 (9k)· London

You will work with Databricks, Microsoft Azure (Data, Infrastructure, AI) services, Azure Data Services, AI Services, and cloud-native technologies. The Global Customer Success Chief Architect’s Office drives adoption of Databricks solutions on the Microsoft platform, leading architecture reviews and designing enterprise-scale data, analytics, and AI solutions.

WNS, a Business Process Management company, seeks a Lead Data Engineer with 10+ years experience to develop features and drive architectural decisions on their cloud delta lakehouse platform using SQL Server, SSIS, T-SQL, Azure Data Factory, ADLS, Azure SQL Database, PySpark, Spark SQL, Databricks, and Delta Lake. The role involves mentoring junior engineers, establishing engineering standards, and leading complex data warehouse initiatives within an agile team in central London.

You will work with Python/PySpark, Databricks, AWS SageMaker, S3, Glue, Lake Formation, IAM, Terraform/CloudFormation/CDK, and Git/CI/CD. As part of a small delivery team, you will migrate ML data pipelines from Databricks to a SageMaker-based MLOps platform for a regulated iGaming client, building production pipelines and proving parity between platforms.

You will work with Databricks, Apache Spark, SQL, Python, Azure DevOps, Git, and CI/CD, applying Medallion Architecture, Delta Lake, CDC, SCD, and dimensional modelling. The role is in a global cybersecurity organisation's AI and Data function, where you will design and build scalable data solutions for analytics, reporting, and AI initiatives.

The Senior Data Engineer (ML) works with Python, PySpark, AWS data and ML stack (S3, Glue, IAM), SageMaker, SQL, Git, CI/CD, and Terraform/CloudFormation/CDK. They are part of a team migrating an ML estate from Databricks (Spark/Delta Lake) to an AWS SageMaker-based MLOps platform for a regulated iGaming environment, building and migrating production data pipelines that feed model training and inference and implementing parity testing.

Migrate ML data pipelines from Databricks (Spark/Delta Lake) to an AWS Sage

You will work with Azure Databricks, PySpark, Python, SQL, Delta Lake, Structured Streaming and CI/CD tooling on a multi-year programme migrating Oracle data platforms to a cloud-native platform. The project supports Endur, global reporting, analytics and risk management for a leading global energy trading organisation while reducing latency to near real-time.

Work with the Databricks Data Intelligence Platform, Spark, PySpark, Python, Java or Scala, and major public cloud platforms (AWS, GCP, Azure). As a pre-sales engineer, you will demonstrate how Databricks' unified data and AI platform helps customers solve complex data challenges, collaborating with Account Executives and Senior Solutions Architects.

Work with Python, PySpark, Spark SQL, T-SQL, Delta Lake, Databricks, Azure Data Factory, and Power BI/Fabric. In Telefónica Tech’s Data Office, you design and build analytics data products across the full platform lifecycle while leading a small engineering team.

Senior Data Engineer role using Python, Databricks (Workflows, Delta Lake, Lakehouse), Spark/PySpark, SQL, and cloud platforms to build and optimise enterprise-scale data pipelines for a major global banking organisation investing in data and analytics.

Design, develop, and optimize data pipelines using SQL, Python, Scala, Java, or Spark, along with ETL/ELT tools like Azure Data Factory, AWS Glue, and Apache Airflow, on cloud platforms such as Azure, AWS, or GCP. You will work with databases (SQL Server, Snowflake, MongoDB), big data technologies (Spark, Kafka, Databricks), and orchestration tools to build scalable cloud-based data platforms supporting enterprise analytics and machine learning.

You will work hands-on daily with Python, SQL, Spark, Databricks/Delta Lake, orchestration tools (Dagster, Airflow, Temporal), dbt, Docker, and CI/CD. You will build and maintain data pipelines for the company's Insights platform, which turns raw financial data into advisory intelligence for commercial banking teams. As a senior engineer, you will set the technical direction for this platform.

Design, build and optimize scalable data pipelines, ETL/ELT processes, and cloud-native data platforms using Microsoft Azure, AWS, or GCP, with tools like Apache Airflow, Azure Data Factory, or AWS Glue, and big data technologies including Apache Spark and Databricks. This London-based senior role partners with data scientists, analytics, and software engineering teams to support enterprise reporting, analytics, and machine learning initiatives.

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.

Build streaming and batch pipelines on Kafka/Redpanda and a time-series store (ideally ClickHouse) with a lakehouse architecture, using Python, SQL, Docker, Terraform, and CI/CD. You will own data contracts, schema evolution, and governance for the Central Data Team building the Keyrock Data Platform that serves trading desks, wealth/asset management, risk, and compliance.