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# Data Engineer

- **Company:** Uk-leading
- **Location:** Hampshire, UK (Remote available)
- **Salary:** £40,000.0 - £80,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Airflow, Amazon Web Services, Big Data, Computer Programming, Continuous Integration, Data Infrastructure, Data Integration, Python (Programming Language), Machine Learning, Cloud Services, AI Infrastructure, Data Ingestion, Sql Optimization, Snowflake, Apache Spark, Generative AI, Git, Pyspark, Infrastructure Automation Frameworks, Performance Monitor, Real Time Data, Terraform, Docker, Jenkins, Databricks
- **Published:** July 17, 2026
- **Apply:** https://www.talentsure.co.uk/job/data-engineer/

## About the Role

To be successful in this role, you will have a genuine passion for building scalable, resilient cloud data platforms alongside the following technical expertise:

 * Platform Experience: Strong, hands-on experience with Databricks or Snowflake on AWS.
 * Programming & Orchestration: Proven Python skills, including deep expertise in PySpark (or Spark) and Airflow.
 * Data Modelling: Advanced SQL skills and extensive experience with end-to-end data modelling.
 * Data Integration: Proven experience building both batch and real-time data integrations.
 * CI/CD & Infrastructure: Hands-on CI/CD experience with Git, Jenkins, or similar tools, along with knowledge of Terraform or equivalent Infrastructure as Code (IaC) tools.
 * Data Ingestion: The ability to successfully ingest, cleanse, and structure large, complex datasets.
 * Desirable Skills: Prior experience with Docker and Kubernetes, or exposure to production-level Generative AI, is highly beneficial.
 * Collaboration: Strong communication and collaboration skills, coupled with a proactive, inquisitive attitude.

## Description

* Data Product Development: Build and support robust data products within a modern, cloud-based data platform.
 * Collaborative Design: Design and deliver innovative data solutions alongside data engineers, scientists, and product teams.
 * Pipeline Optimisation: Develop, maintain, and optimize scalable data pipelines across the analytics platform.
 * Data Integration: Integrate large, diverse datasets from various sources while maintaining exceptionally high quality and governance standards.
 * Platform Orchestration: Maintain the orchestration, proactive monitoring, and general performance of data platform components.
 * Engineering Excellence: Champion high coding and data practice standards, helping to improve engineering processes across the wider data community.
 * Innovation: Experiment with emerging data, machine learning (ML), and generative AI technologies to drive business value.
 * Architectural Partnership: Partner with data architects on the high-level design of data products.
 * Agile Squads: Work collaboratively within multi-functional agile squads.
 * AI Infrastructure: Support machine learning and GenAI infrastructure and end-to-end workflows.


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