Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Здесь есть сильная техническая и лидерская составляющая, но вместе с ней нужно вести клиентские задачи, поддерживать продажи, нанимать людей и развивать публичность. Зарплата не указана, поэтому оценить финансовую сторону предложения сложно.
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Описание вакансии
Текст:
Hirify AI/Оригинал
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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