4 дня назад
Lead Data Engineer (GCP)
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Lead Data Engineer (GCP): Designing and delivering scalable, resilient data platforms and batch and streaming pipelines on Google Cloud with an accent on BigQuery data modelling, production-grade Python and SQL, and engineering standards. Focus on owning architecture decisions, embedding data quality and observability, resolving complex data engineering problems, and mentoring engineers across the team.
Location: Hybrid role requiring attendance at least 3 days a week at GSIQ in Solihull, United Kingdom
Company
is a rapidly growing fitness and conditioning apparel company building products and experiences for a global community.
What you will do
- Own the technical design and architecture of scalable data pipelines, data models, and platform components.
- Set engineering standards for code quality, testing, observability, security, and documentation.
- Lead technical discovery, design sessions, code reviews, and architecture decisions.
- Build and improve batch and streaming data platforms using the GCP ecosystem.
- Embed data quality, access control, privacy, monitoring, and alerting into engineering work.
- Mentor Data Engineers, facilitate knowledge sharing, support hiring, and collaborate with Data Governance, Data Product, and wider Tech teams.
Requirements
- Strong data engineering experience in a senior or lead-level technical role.
- Deep expertise in GCP, including BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Cloud Composer.
- Advanced Python and SQL skills, including performant production code and rigorous code reviews.
- Experience designing complex scalable pipelines using batch and streaming or event-driven patterns.
- Strong data modelling experience with dimensional modelling, Data Vault, or equivalent, plus Dataform or similar SQL-based transformation tools.
- Experience with CI/CD, Git, testing frameworks, Terraform, data quality, observability, technical leadership, mentoring, and stakeholder management.
Nice to have
- DataProc and Spark experience for large-scale distributed processing.
- Looker or similar BI tooling and familiarity with analytics engineering practices.
- Experience with data contracts, semantic layers, data mesh, or data platform architecture patterns.
- GCP cost management, BigQuery cost optimisation, ML infrastructure, feature engineering, or data science platform enablement.
- Experience in e-commerce or retail data environments.
Culture & Benefits
- Performance-based bonus opportunity.
- Funded healthcare, contributory employer pension, life assurance, and enhanced family leave.
- 25 days of holiday, an additional birthday day, and bank holidays.
- Flexible benefits including an electric vehicle salary-sacrifice scheme, dental insurance, cycle-to-work scheme, technology scheme, and holiday trading.
- employee discount, long-service awards, cashback and discounts, and wellbeing support.
- Office-specific benefits include gym membership, onsite lunch and coffee bars, and electric vehicle charging points.
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