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6 дней назад

Principal Data Engineer (Data Practice Lead)

Формат работы
remote (только United_kingdom)/onsite
Тип работы
fulltime
Грейд
senior/lead
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Principal Data Engineer (Data Practice Lead) (Data Engineering/AI): Building and leading YLD's data practice through hands-on delivery of pipelines, transformation layers, data models, and infrastructure across client environments with an accent on technical leadership, client-facing consultancy, and AI-native data engineering. Focus on designing reliable and cost-conscious data platforms, solving complex architecture and governance problems, and shaping proposals, standards, and team capability.

Location: London, United Kingdom. Remote-first working is available, with regular travel to client sites, workshops, and industry events.

Company

hirify.global is a software engineering and product design consultancy founded in 2013, headquartered in London, with delivery teams in Lisbon and Porto.

What you will do

  • Perform hands-on data engineering across pipelines, transformation layers, models, and supporting infrastructure.
  • Deliver data solutions across legacy warehouse migrations, greenfield lakehouses, and transformation platforms.
  • Act as the technical authority in client and prospect meetings, shaping proposals, pitches, and engagement scope.
  • Set internal standards for testing, documentation, project structure, code review, and data reliability.
  • Mentor data engineers and guide teams through complex technical decisions and escalations.
  • Build hirify.global's data practice through hiring, sales support, external events, and community activity.

Requirements

  • Strong background as a data engineer or data lead with a track record of technical leadership.
  • Client- or stakeholder-facing experience, with the ability to present to senior stakeholders and translate engineering constraints into business terms.
  • Production experience with SQL, typed and testable Python, data modelling, transformation architecture, and pipeline design.
  • Experience with data testing, observability, CI/CD, infrastructure as code, governance, lineage, access control, and cost optimisation.
  • Platform fluency across tools such as Airflow, Dagster, Snowflake, BigQuery, Databricks, Fivetran, Airbyte, dbt, and Spark.
  • Experience with AI-native engineering workflows and constructs such as RAG, semantic search, evaluations, and guardrails.

Nice to have

  • Consulting or agency experience.
  • Existing public presence in the data community.

Culture & Benefits

  • Remote-first environment with flexible working and work-life balance.
  • Private health care, company pension scheme, and enhanced paid maternity and paternity leave.
  • 25 days of annual holiday excluding public holidays.
  • £2,000 annual training and conference allowance plus £300 additional hardware allowance.
  • Mental health support, company laptop, performance-related bonus, and referral schemes.
  • Values focused on continuous growth, inclusion, honesty, ethical relationships, inspiring solutions, and collaboration.

Hiring process

  • Screening call with the Talent team.
  • Introductory conversation and technical conversation with engineering and data leadership.
  • Final interview with the leadership team.

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