Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Современный стекКлиматические технологииПонятные задачиЭтап роста
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Analytics Engineer (Data Pipelines/AI): Building, scaling, and optimizing production data pipelines with Prefect, dbt, ClickHouse, and Metabase to support data-driven decisions, with an accent on standardized ingestion, testing, and data quality. Focus on improving documentation and semantics for AI adoption, modeling business data, and solving stakeholder questions through reliable datasets.
Location: Hybrid, based at the Utrecht office with regular attendance in Utrecht or Amsterdam; approximately 60% of work is from home.
Company
hirify.global provides a smart monitoring platform for industry that uses data insights and automation to help manufacturers reduce energy waste, costs, and carbon emissions; the company has joined forces with ABB.
What you will do
Build, scale, and optimize production data pipelines with Prefect, extracting data from internal and external sources.
Model data with dbt on ClickHouse to enable meaningful visualizations in Metabase.
Standardize data ingestion into the data warehouse so new sources follow a consistent implementation path.
Improve testing practices across data pipelines to provide high-quality datasets and detect data changes proactively.
Drive AI adoption through better documentation, clearer semantics, and richer data context.
Work with stakeholders, data engineers, analysts, and data scientists to identify data gaps and determine useful solutions.
Requirements
3+ years of experience building and maintaining production data pipelines.
Strong SQL skills for writing readable and maintainable queries that leverage underlying data architecture.
Proactive and pragmatic problem-solving approach.
Familiarity with cloud data warehouses such as ClickHouse, Snowflake, or BigQuery.
Experience with data orchestration tools such as Prefect, Airflow, or Dagster.
Familiarity with professional software engineering practices, including version control, merge requests, testing, code standards, and CI/CD.
Experience with cloud platforms such as AWS or GCP.
Culture & Benefits
Work in a small analytics team within a high-growth scale-up.
Work closely with stakeholders and technical data teams, independently picking up projects.
Share knowledge, discuss technical solutions, and review code with colleagues.
Use two-week sprints with planning, retrospectives, and daily standups.
Work from home approximately 60% of the time and meet regularly in the Utrecht or Amsterdam office.
Use Linear, Miro, Google Drive, Outline, and Slack for collaboration and communication.
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