Senior Data Engineer at Primark in Reading, , United Kingdom

Job description

• We are seeking a Senior Data Engineer to join Primark’s Data Platform & Engineering team, leading the design and delivery of scalable data solutions on our Databricks-based enterprise platform. You will build and optimise trusted data products that power reporting, analytics, AI and data science across the business. Working closely with engineering, analytics and business teams, you will provide technical leadership, mentor Data Engineers and drive engineering best practices. This is a hands-on role for an experienced engineer with deep expertise in Databricks, dbt Cloud, Spark and SQL, who is passionate about delivering high-quality data solutions. You will play a key role in Primark’s migration from Teradata to Databricks and the ongoing evolution of our Data & Analytics capabilities.

Responsibilities

• 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.

Requirements

• 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.

Skills

Required

• Databricks
• PySpark
• SQL
• dbt Cloud or dbt Core
• Azure
• Data pipeline design and optimisation
• Data modelling
• Data quality and observability
• Performance tuning
• CI/CD and version control
• Technical leadership
• Stakeholder engagement