Analytics Engineer (DBT, BigQuery)
⚲ Warszawa, Wola
16 500–19 000 zł brutto / mies.
Wymagania
- dbt
- Python
- Prefect
- Airflow
- Dagster
- BigQuery
Opis stanowiska
Nasze wymagania:
3+ years of experience in analytics engineering, data engineering or a comparable data role, working with large amounts of data
Expert in SQL - able to write and review complex queries with confidence
Solid understanding of data modeling principles and hands-on experience with dbt or a comparable transformation framework
Engineering discipline applied to analytics code: version control, code review, testing, and CI are your defaults, and you can bring a team along to work the same way
Comfortable with Python, with experience in a workflow orchestration tool (Prefect, Airflow, Dagster)
Experience with a cloud data warehouse; BigQuery is a plus
Experience supporting and working with cross-functional teams in a dynamic environment
A proactive mindset - you look for improvements before anyone asks, and you challenge the status quo when you see a better way
Mile widziane:
Experience in enterprise security or authentication domains.
Familiarity with zero trust models and device security posture management.
Experience with Kubernetes and cloud platforms like GCP, AWS, or Azure.
Experience with PHP, TypeScript and React.
Prior experience working on internal platforms or systems that require high reliability and compliance
O projekcie:
Business Analytics at Box is growing, and with it the need for a consistent and trusted data foundation for decision-making at scale. As an Analytics Engineer you will develop and own that foundation: well-designed data models and pipelines, governed metric definitions, systematic testing and quality monitoring, and standards that enable the team to build on it consistently. You will also build workflows and automations that let our data products meet our stakeholders where they are, from Slack to Salesforce.
Zakres obowiązków:
Evolve our dbt project toward modular, documented and tested data models organized in clear layers, from raw sources to marts
Shape our semantic layer from its early stages: define how metrics are modeled and governed, and drive its adoption
Shape the data modeling standards and conventions for the Business Analytics team, and uphold them through code review, pairing, and documentation
Partner with Data Scientists and Data Analysts to design the datasets their analyses, dashboards, and ML models are built on
Build out our data testing practices and enforce them in CI, implement observability over our data
Diagnose upstream data issues and drive them to resolution by partnering with Data Engineering and Enterprise Systems teams
Build and maintain the Prefect workflows that put our data and models to work
3+ years of experience in analytics engineering, data engineering or a comparable data role, working with large amounts of data
Expert in SQL - able to write and review complex queries with confidence
Solid understanding of data modeling principles and hands-on experience with dbt or a comparable transformation framework
Engineering discipline applied to analytics code: version control, code review, testing, and CI are your defaults, and you can bring a team along to work the same way
Comfortable with Python, with experience in a workflow orchestration tool (Prefect, Airflow, Dagster)
Experience with a cloud data warehouse; BigQuery is a plus
Experience supporting and working with cross-functional teams in a dynamic environment
A proactive mindset - you look for improvements before anyone asks, and you challenge the status quo when you see a better way
Mile widziane:
Experience in enterprise security or authentication domains.
Familiarity with zero trust models and device security posture management.
Experience with Kubernetes and cloud platforms like GCP, AWS, or Azure.
Experience with PHP, TypeScript and React.
Prior experience working on internal platforms or systems that require high reliability and compliance
O projekcie:
Business Analytics at Box is growing, and with it the need for a consistent and trusted data foundation for decision-making at scale. As an Analytics Engineer you will develop and own that foundation: well-designed data models and pipelines, governed metric definitions, systematic testing and quality monitoring, and standards that enable the team to build on it consistently. You will also build workflows and automations that let our data products meet our stakeholders where they are, from Slack to Salesforce.
Zakres obowiązków:
Evolve our dbt project toward modular, documented and tested data models organized in clear layers, from raw sources to marts
Shape our semantic layer from its early stages: define how metrics are modeled and governed, and drive its adoption
Shape the data modeling standards and conventions for the Business Analytics team, and uphold them through code review, pairing, and documentation
Partner with Data Scientists and Data Analysts to design the datasets their analyses, dashboards, and ML models are built on
Build out our data testing practices and enforce them in CI, implement observability over our data
Diagnose upstream data issues and drive them to resolution by partnering with Data Engineering and Enterprise Systems teams
Build and maintain the Prefect workflows that put our data and models to work
🔍 Dekoder Ogłoszenia
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Engineering discipline applied to analytics code: version control, code review, testing, and CI are your defaults, and you can bring a team along to work the same way
Oczekuje się, że będziesz wdrażać i egzekwować najlepsze praktyki inżynierskie w kodzie analitycznym, a także szkolić innych członków zespołu.
🔴
Comfortable with Python, with experience in a workflow orchestration tool (Prefect, Airflow, Dagster)
Oprócz SQL, oczekuje się biegłości w Pythonie i umiejętności pracy z narzędziami do orkiestracji przepływów pracy, co może wykraczać poza typowe zadania analityka.
🔴
Experience supporting and working with cross-functional teams in a dynamic environment
Może oznaczać częste zmiany priorytetów, konieczność szybkiego reagowania na potrzeby różnych działów i potencjalnie nieprzewidywalne środowisko pracy.
🟡
A proactive mindset - you look for improvements before anyone asks, and you challenge the status quo when you see a better way
Oczekuje się, że będziesz samodzielnie identyfikować problemy i proponować rozwiązania, co może wiązać się z koniecznością przekonywania innych do swoich pomysłów.
🔴
Prior experience working on internal platforms or systems that require high reliability and compliance
Może oznaczać pracę z systemami o wysokich wymaganiach regulacyjnych i bezpieczeństwa, co może generować dodatkową złożoność i biurokrację.