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5 дней назад

Principal Data Engineer

Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Principal Data Engineer (Python/SQL/Cloud Data Platforms): Designing and evolving scalable data platforms and production-grade pipelines with an accent on distributed processing, cloud-native architecture, data quality, and platform reliability. Focus on leading cross-team architecture decisions, building observable and cost-efficient systems, and raising engineering standards across multiple squads.

Location: Hybrid role based in Southampton or London, England, with around 20% of Engineering time involving in-person collaboration.

Company

hirify.global is a home improvement retailer operating brands including B&Q, Screwfix, Brico Depot, Castorama and Koctas, with more than 74,000 people.

What you will do

  • Define and drive the data platform and data engineering strategy in line with Group Technology objectives.
  • Lead architecture decisions and establish scalable standards and design patterns for data pipelines, storage and processing.
  • Design and deliver scalable, resilient, observable and cost-efficient data platforms and production pipelines.
  • Partner with Architecture and Product teams on long-term platform roadmaps and capabilities.
  • Strengthen data quality, governance, security and reusable data products while promoting CI/CD, testing, DevOps, DataOps and platform automation.
  • Lead multi-team initiatives, influence senior stakeholders, coach engineers, support hiring and evaluate emerging technologies.

Requirements

  • Deep expertise in distributed data processing, cloud-native systems and modern data architecture.
  • Proven experience delivering large-scale data platforms and production-grade pipelines.
  • Strong Python and SQL skills, with hands-on experience in Spark, PySpark or Scala.
  • Experience with dbt for data modelling and transformation.
  • Strong knowledge of GCP, Azure or AWS, including services such as Databricks, BigQuery or Azure Data Factory.
  • Strong understanding of DevOps and DataOps practices and tools, including CI/CD, Git, Terraform, Docker and Kubernetes.
  • Experience with data quality tools and testing frameworks such as Great Expectations.
  • Deep understanding of batch, streaming and event-driven architecture patterns, including resilient, scalable and observable system design and performance and cost optimisation.
  • Track record of setting engineering standards, driving continuous improvement, influencing strategic and investment decisions, working through ambiguity, and coaching engineers.

Culture & Benefits

  • Hybrid working model balancing home working with office and offsite collaboration.
  • Inclusive environment focused on experimentation, new ideas, diversity and equal treatment.
  • Private healthcare, pension scheme, life assurance and competitive bonus scheme.
  • 25 days’ holiday plus bank holidays, staff discounts and share incentive and share-save plans.
  • Opportunities for career development, mentoring and participation in a wider Data Engineering community.

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