Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
Senior Data Engineer builds and maintains scalable data pipelines and platform components in Python/Scala with Spark, Azure, and Databricks to power analytics and ML at ASOS.
Build and own cloud-native data and ML pipelines using Python and PySpark in a hybrid role focused on AI platform engineering.
Design and deliver scalable data platforms and pipelines for clients in regulated sectors like banking and life sciences, enabling AI and analytics use cases.
Design and implement scalable Azure-based ETL pipelines and data flows for a UK fintech firm, using Azure Data Factory, Synapse, and Spark to improve financial well-being analytics.
Lead the design and delivery of a modern cloud-based data platform for a major UK retailer using Azure, Databricks, PySpark, and Python to build scalable pipelines and mentor engineers.
Principal Data Engineer builds and maintains Azure Databricks pipelines, ELT workflows, and production AI models to power analytics and insights for England’s higher-education regulator.
Build and maintain data pipelines and integrations for a B2B SaaS product using Python, SQL, PySpark, and Databricks to deliver clean, reliable data to client workflows.
Principal Data Engineer builds and secures Azure-based data platforms (ADF, Databricks, Lakehouse) to power real-world decision-making and modernize large-scale systems.
Principal Data Engineer at Royal London designs and builds scalable data pipelines and platforms using Python, SQL, Databricks, and Azure tools to enable AI-driven insights for pensions and investments.
Build and maintain cloud data pipelines on AWS, transform data in Snowflake with dbt and PySpark, and deliver analytics for regulated industries like banking and healthcare.
Build secure, scalable data pipelines and platforms for government clients, transforming sensitive data into trusted assets for analytics and AI using Python, SQL, and cloud tools.
Build and own cloud-native data and ML pipelines end-to-end for an AI-first SaaS platform that turns messy data into trusted insights.
Build and optimize PySpark pipelines and lakehouse architectures on AWS/Azure/GCP while collaborating with clients to deliver scalable data solutions.
Design and build scalable Azure data pipelines, migrate legacy systems to the cloud, and optimize ETL/ELT processes using Databricks, PySpark, and Azure Data Factory.
Build and maintain Azure-based data pipelines, lakes, and warehouses, and deliver Power BI reports to support scalable analytics and business intelligence.
Build and scale cloud-native data pipelines on Azure and Databricks, owning production-grade systems and setting engineering standards for a major UK retail brand.
Principal Data Engineer builds and leads data pipelines and foundations using Databricks, PySpark, Python and SQL to enable an energy trading company to extract value from data.
Builds and maintains Azure-based data pipelines and ELT/ETL processes using Azure Data Factory, Synapse, and Fabric to deliver clean datasets for analytics and reporting.
Lead a team of data engineers to design and deliver secure, scalable data solutions for critical energy and infrastructure projects, using cloud platforms and modern data practices.
Build and maintain data pipelines, warehouses, and lakes to ensure accurate, accessible, and secure data processing using Python, PySpark, SQL, and Java.
We couldn't check your fit for this role — add a CV to your profile to see it next time.