<?xml version="1.0" encoding="utf-8"?>
<rss version="2.0">
  <channel>
    <title>Data Engineer (SQL and PySpark) - Matchtech RSS Feed</title>
    <link>https://jobs.co.uk/job/data-engineer-sql-and-pyspark-matchtech--aaa5376b-8368-4f52-9863-78ffc7329bed</link>
    <description>RSS feed for Data Engineer (SQL and PySpark) at Matchtech.</description>
    <language>en-gb</language>
    <lastBuildDate>Thu, 18 Jun 2026 14:16:25 GMT</lastBuildDate>
    <item>
      <title>Data Engineer (SQL and PySpark) - Matchtech</title>
      <link>https://jobs.co.uk/job/data-engineer-sql-and-pyspark-matchtech--aaa5376b-8368-4f52-9863-78ffc7329bed</link>
      <guid>https://jobs.co.uk/job/data-engineer-sql-and-pyspark-matchtech--aaa5376b-8368-4f52-9863-78ffc7329bed</guid>
      <pubDate>Thu, 18 Jun 2026 11:52:07 GMT</pubDate>
      <description>Location: Dunstable | Salary: 549.00-549.00 Daily | Type: Contract | Data EngineerLocation: Dunstable (near Luton) - Hybrid (up to 2 days onsite) Rate: 549 per day (Inside IR35 / Umbrella) Contract: Initial term until end of AugustOverviewWhitbread is seeking a hands-on Data Engineer to build and maintain scalable, production-grade data pipelines within reusable, modular frameworks. This role focuses on engineering high-quality, durable solutions rather than one-off development.Key ResponsibilitiesDesign and develop end-to-end data pipelines using reusable frameworksBuild scalable data solutions using Python, SQL, and PySparkCreate modular frameworks separating configuration from orchestrationImplement robust automated testing (unit, integration, regression)Establish and enforce data quality controls (schema, nulls, row counts, integrity checks)Contribute to CI/CD pipelines and Git-based workflowsTroubleshoot and optimise data pipelines for reliability and performanceRequired ExperienceStrong Data Engineering backgroundAdvanced Python and SQL skillsExperience with PySpark or distributed processing toolsProven track record building reusable data frameworksStrong testing experience (pytest, mock data, data validation techniques)Solid understanding of ...</description>
      <category>Contract</category>
    </item>
  </channel>
</rss>