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Primark

Fast-fashion retailer with affordable apparel

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeReading, UKNo salary listedHybrid

About the Job

Requirements

  • Strong hands-on experience designing, building, and optimizing enterprise-scale data pipelines and data platforms using Databricks, PySpark, and advanced SQL.
  • Proven experience with Azure-based data technologies and designing scalable lakehouse architectures, data models, and modern cloud data solutions.
  • Experience with dbt Cloud or dbt Core, including model development, testing, documentation, lineage, deployment workflows, continuous integration and continuous delivery, and version control practices.
  • Strong understanding of data quality, observability, operational monitoring, and performance tuning, focused on reliable, scalable, and cost-efficient data solutions.
  • Demonstrated success delivering data products that support analytics, reporting, artificial intelligence, and data science use cases, driving measurable business outcomes and value creation.
  • Ability to provide technical leadership, translate business requirements into scalable solutions, and collaborate across Engineering, Analytics, Governance, Architecture, and business teams.
  • Experience coaching engineers, sharing best practices, and driving continuous improvement across data engineering teams.

Responsibilities

  • Design, build, and optimize scalable data pipelines, ETL/ELT workflows, and data transformation solutions using Databricks, PySpark, SQL, and dbt Cloud, delivering trusted, high-quality data products that support reporting, analytics, artificial intelligence, and data science.
  • Develop and maintain robust lakehouse architectures and reusable data models, ensuring solutions are scalable, performant, secure, and aligned with enterprise data standards.
  • Lead engineering initiatives and establish best practices and high standards across development, testing, deployment, documentation, and monitoring, while advancing automation and continuous integration and continuous delivery adoption.
  • Provide technical guidance, conduct code reviews, and mentor Data Engineers to strengthen engineering capability, promote knowledge sharing, and foster continuous improvement.
  • Support Primark’s migration from Teradata to Databricks, including data remodelling, pipeline migration, performance optimization, and ongoing evolution of the enterprise data platform.
  • Partner with Analytics, Data Science, Governance, and business stakeholders to translate requirements into scalable technical solutions and reusable datasets that deliver measurable business value.
  • Identify opportunities to improve platform performance, scalability, and cost efficiency, and contribute to engineering standards, roadmap initiatives, and the long-term growth of Primark’s Data & Analytics capabilities.

About the Company

Primark

Fast-fashion retailer with affordable apparel

Primark is a fashion and home retailer with a focus on affordable, everyday style. It carries a wide range of products including clothing for babies, kids, women, and men, plus home goods, accessories, beauty items, and confectionery, sold in its many stores across Europe and in the United States. Customers shop in brick-and-mortar stores, where goods move quickly and prices stay low to reflect Primark’s value-focused model. The company differentiates itself by offering a broad, multi-category assortment at low prices, relying on a fast-paced store network and frequent product turnover to keep fashion affordable. Its goal is to help people access stylish looks and everyday essentials at great prices, while expanding its presence especially in the United States.

Company size
10,001+
Company stage
Not listed
Total funding
Not listed
Headquarters
Dublin, Ireland
Founded
1969

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