What you'll do
Data Engineering Delivery: Design, build and optimise 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, AI and data science.
Data Architecture & Modelling: Develop and maintain robust lakehouse architectures and reusable data models, ensuring solutions are scalable, performant, secure and aligned with enterprise data standards.
Technical Leadership & Engineering Excellence: Lead engineering initiatives, establish best practices and drive high standards across development, testing, deployment, documentation and monitoring, while championing automation and CI/CD adoption.
Code Quality & Team Mentorship: Provide technical guidance, conduct code reviews and mentor Data Engineers to strengthen engineering capability, promote knowledge sharing and foster a culture of continuous improvement.
Platform Modernisation: Play a key role in Primark’s migration from Teradata to Databricks, supporting data remodelling, pipeline migration, performance optimisation and the ongoing evolution of the enterprise data platform.
Data Product Delivery & Stakeholder Collaboration: Partner with Analytics, Data Science, Governance and business stakeholders to translate requirements into scalable technical solutions and reusable datasets that deliver measurable business value.
Continuous Improvement & Strategic Contribution: Identify opportunities to improve platform performance, scalability and cost efficiency, while contributing to engineering standards, roadmap initiatives and the long-term growth of Primark’s Data & Analytics capabilities.
What you'll bring
Advanced Data Engineering Experience (5-8 Years): Strong hands-on experience designing, building and optimising enterprise-scale data pipelines and data platforms using Databricks, PySpark and advanced SQL.
Cloud Data Platforms & Architecture: Proven experience working with Azure-based data technologies and designing scalable lakehouse architectures, data models and modern cloud data solutions.
dbt & Engineering Best Practices: Experience with dbt Cloud or dbt Core, including model development, testing, documentation, lineage, deployment workflows, CI/CD and version control practices.
Data Quality, Performance & Optimisation: Strong understanding of data quality, observability, operational monitoring and performance tuning, with a focus on delivering reliable, scalable and cost-efficient data solutions.
Data Product Delivery & Commercial Value: Demonstrated success delivering data products that support analytics, reporting, AI and data science use cases, driving measurable business outcomes and value creation.
Technical Leadership & Stakeholder Engagement: Ability to provide technical leadership, translate business requirements into scalable solutions and collaborate effectively across Engineering, Analytics, Governance, Architecture and business teams.
Mentoring & Continuous Improvement: Experience coaching engineers, sharing best practices and driving continuous improvement across data engineering teams.
About Primark
At Primark, people matter. They’re the beating heart of our business and the reason we’ve grown from our first store in Dublin in 1969 to a £9bn+ turnover business and over 80,000 colleagues and over 440 stores in 17 countries today. Our values run through everything we do. In essence, we're Caring and always strive to put people first. We're also Dynamic, bravely pushing the boundaries to stay ahead. And finally, we succeed Together.
If you need any reasonable adjustments or have an accessibility request, during your recruitment journey, such as extended time or breaks between online assessments, a sign language interpreter, mobility access, or assistive technology please contact your talent acquisition specialist.
All offers of employment are subject to background checks, including right to work, reference education and for some roles criminal, and financial checks. If you have any concerns, please reach out to our talent acquisition team to discuss.