Senior Data Consultant
⚲ Kraków, Poznan, Wrocław, Łódź, Warszawa
21 000 - 26 880 PLN (B2B)
Wymagania
- Data engineering
- SQL
- Python
- Data modelling
- Data warehouse
- Data Lake
- GCP
- dbt
- Airflow
- Trino
- CI/CD
- Data pipelines
- BigQuery
- Bi tools (nice to have)
- Power BI (nice to have)
- Qlik (nice to have)
- Apache Superset (nice to have)
- Snowflake (nice to have)
- Databricks (nice to have)
- Spark (nice to have)
- PySpark (nice to have)
Opis stanowiska
O projekcie:
What will you do?
Join a team focused on building and evolving modern cloud-based data platforms and analytical solutions. You will design and develop scalable data pipelines, data models, and transformation processes, enabling efficient data consumption across business and technology teams while supporting data-driven decision-making.
Wymagania:
- 5+ years of commercial experience as a Data Engineer- Strong SQL, Python- Experience with data modelling- Knowledge of data warehousing, data lakes and data lakehouse concepts- Hands-on experience with GCP data engineering tools- Very good knowledge of BigQuery- Experience with DBT, Airflow and Trino- Understanding of CI/CD practices and automation- Experience designing and implementing scalable data pipelines
Nice to have
- Experience with Spark/PySpark- Experience with BI tools such as Power BI, Qlik or Apache Superset- Experience with Snowflake- Experience with Databricks
Codzienne zadania:
- Design, build, test and deploy cloud and on-premise data models and transformations
- Develop and maintain ETL processes and data pipelines
- Optimize data views and storage structures for analytics and visualization use cases
- Review, refine and implement business and technical requirements
- Collaborate on backlog management, user story refinement and sprint planning activities
- Onboard new data sources and develop data ingestion frameworks
- Design, build, test and deploy cloud data warehouses and data products
- Ensure data quality, performance, reliability and scalability across solutions
What will you do?
Join a team focused on building and evolving modern cloud-based data platforms and analytical solutions. You will design and develop scalable data pipelines, data models, and transformation processes, enabling efficient data consumption across business and technology teams while supporting data-driven decision-making.
Wymagania:
- 5+ years of commercial experience as a Data Engineer- Strong SQL, Python- Experience with data modelling- Knowledge of data warehousing, data lakes and data lakehouse concepts- Hands-on experience with GCP data engineering tools- Very good knowledge of BigQuery- Experience with DBT, Airflow and Trino- Understanding of CI/CD practices and automation- Experience designing and implementing scalable data pipelines
Nice to have
- Experience with Spark/PySpark- Experience with BI tools such as Power BI, Qlik or Apache Superset- Experience with Snowflake- Experience with Databricks
Codzienne zadania:
- Design, build, test and deploy cloud and on-premise data models and transformations
- Develop and maintain ETL processes and data pipelines
- Optimize data views and storage structures for analytics and visualization use cases
- Review, refine and implement business and technical requirements
- Collaborate on backlog management, user story refinement and sprint planning activities
- Onboard new data sources and develop data ingestion frameworks
- Design, build, test and deploy cloud data warehouses and data products
- Ensure data quality, performance, reliability and scalability across solutions
🔍 Dekoder Ogłoszenia
🔴
Join a team focused on building and evolving modern cloud-based data platforms and analytical solutions.
Może oznaczać, że zespół jest w fazie tworzenia lub przebudowy, co wiąże się z niepewnością i potencjalnymi zmianami priorytetów.
🔴
You will design and develop scalable data pipelines, data models, and transformation processes, enabling efficient data consumption across business and technology teams while supporting data-driven decision-making.
Choć brzmi to jak standardowe zadania, 'scalable' może oznaczać, że obecne rozwiązania nie są skalowalne i będziesz musiał je naprawić, a nie budować od zera.
🔴
Codzienne zadania: Design, build, test and deploy cloud and on-premise data models and transformations
Wspominanie o 'on-premise' obok 'cloud' może sugerować, że będziesz musiał pracować z przestarzałą infrastrukturą lub integrować nowe rozwiązania z istniejącymi, mniej nowoczesnymi systemami.
🟡
Collaborate on backlog management, user story refinement and sprint planning activities
Może oznaczać, że będziesz miał wpływ na procesy, ale równie dobrze może to być standardowa część pracy w metodyce Agile, gdzie faktyczny wpływ jest ograniczony.
🔴
Ensur
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