Senior Data Architect
⚲ Warszawa
22 000 - 26 000 PLN (PERMANENT)
Wymagania
- Azure
Opis stanowiska
Wymagania:
You will:
- Own and lead technical implementation of well-integrated, re-usable data models and analytics products- Collect and manage data requirements, translating them into technical concepts focused on re-usability and cost efficiency- Ensure best-practice data management and quality assurance processes are defined and applied- Collaborate with data architects, analytics leads and data scientists to ensure sustainable pipelines and analytical products- Partner with business functions and IT teams to ensure delivery aligned with business priorities- Lead integration of diverse data sources to develop globally harmonized data models and KPIs- Steer delivery teams (internal and external), providing estimations and ensuring high-quality delivery
You bring:
- Bachelor's/Master's degree in Computer Science, Engineering or similar- 5+ years of experience in Data & Analytics- Strong data architecture and engineering skills in Spark-based processing (Azure Data Factory, Azure Databricks, SQL, Python)- Proficiency in data modeling, with the ability to mentor data engineers in best practices- Strong knowledge of Tableau or Power BI, and data management practices- Experience with GitHub- Experience delivering data as a product and leading data engineering teams- Knowledge of commercial domain data- Experience applying Agile methodologies- Strong problem-solving, analytical and communication skills- Fluent English, intercultural awareness
You will:
- Own and lead technical implementation of well-integrated, re-usable data models and analytics products- Collect and manage data requirements, translating them into technical concepts focused on re-usability and cost efficiency- Ensure best-practice data management and quality assurance processes are defined and applied- Collaborate with data architects, analytics leads and data scientists to ensure sustainable pipelines and analytical products- Partner with business functions and IT teams to ensure delivery aligned with business priorities- Lead integration of diverse data sources to develop globally harmonized data models and KPIs- Steer delivery teams (internal and external), providing estimations and ensuring high-quality delivery
You bring:
- Bachelor's/Master's degree in Computer Science, Engineering or similar- 5+ years of experience in Data & Analytics- Strong data architecture and engineering skills in Spark-based processing (Azure Data Factory, Azure Databricks, SQL, Python)- Proficiency in data modeling, with the ability to mentor data engineers in best practices- Strong knowledge of Tableau or Power BI, and data management practices- Experience with GitHub- Experience delivering data as a product and leading data engineering teams- Knowledge of commercial domain data- Experience applying Agile methodologies- Strong problem-solving, analytical and communication skills- Fluent English, intercultural awareness
🔍 Dekoder Ogłoszenia
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Own and lead technical implementation of well-integrated, re-usable data models and analytics products
Oczekuje się, że będziesz samodzielnie podejmować decyzje techniczne i brać pełną odpowiedzialność za projekty, często bez wsparcia ze strony przełożonych.
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Collect and manage data requirements, translating them into technical concepts focused on re-usability and cost efficiency
Może oznaczać, że będziesz musiał negocjować z różnymi działami biznesowymi, które mają sprzeczne wymagania, a także szukać kompromisów między jakością a budżetem.
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Collaborate with data architects, analytics leads and data scientists to ensure sustainable pipelines and analytical products
Współpraca może być utrudniona przez różne priorytety i metody pracy poszczególnych zespołów, co może prowadzić do konfliktów.
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Partner with business functions and IT teams to ensure delivery aligned with business priorities
Może oznaczać, że będziesz musiał często zmieniać priorytety i dostosowywać się do pilnych, często zmieniających się potrzeb biznesowych.
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Lead integration of diverse data sources to develop globally harmonized data models and KPIs
Integracja różnorodnych źródeł danych, zwłaszcza w skali globalnej, może być bardzo złożona i czasochłonna, z potencjalnymi problemami z jakością i spójnością danych.