5 дней назад
Head of Data Engineering
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Head of Data Engineering (Data Engineering/Analytics): Leading end-to-end data engineering from ingestion through warehouse design, modelling, and metric reporting with an accent on reliable analytics infrastructure, data quality, and stakeholder alignment. Focus on developing agentic analytics, scaling self-service reporting, managing orchestration and access controls, and mentoring a team of Data Engineers.
Location: London, hybrid
Company
's Data & Analytics function supports business-critical insights, reporting, and data consumption across the organisation.
What you will do
- Own the long-term Data Engineering Strategy and align quarterly roadmaps and OKRs with company objectives.
- Lead two Data Engineers while combining hands-on technical work with strategic leadership and mentoring.
- Develop an agentic analytics framework and enable reliable, scalable self-service analytics.
- Manage data orchestration, ETL, live reporting, data-source integrations, and downstream KPI delivery.
- Establish monitoring, alerting, and data-integrity processes covering metric shifts, staleness, and operational issues.
- Partner with engineering, analytics, regulatory, vendor, and infrastructure stakeholders while promoting data literacy and secure data access.
Requirements
- Advanced SQL skills for both production-grade and analytical use in a commercial environment.
- Proven experience extracting, transforming, and loading data across disparate environments.
- Hands-on experience creating data views in major BI tools such as Looker, Power BI, Tableau, or MicroStrategy.
- Experience leading or managing high-functioning technical talent.
- Deep knowledge of data engineering best practices and modern consumption-layer design.
- Pragmatic, curious, self-driven, and commercially minded approach with measurable delivery impact.
Nice to have
- Python skills.
- Experience with dbt or LookML.
- Knowledge of software development best practices.
- Experience in a digital healthcare environment.
Culture & Benefits
- Permanent employment in a hybrid London workplace.
- Cross-functional collaboration with Data Engineers, Analytical Business Partners, Data Scientists, engineers, regulatory professionals, and external partners.
- Learning culture supported by documentation, training, helpdesk support, newsletters, and lunch-and-learn sessions.
- Focus on data literacy so employees can use data effectively across the organisation.
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