Data Engineer – AI-Accelerated Development (Snowflake, Airflow, Python)
⚲ Warsaw, Krakow, Wroclaw, Poznan, Gdansk, Bialystok
Do uzgodnienia
Wymagania
- Python
- Snowflake
- Airflow
- SQL
Opis stanowiska
At the AI&Data, we work locally and globally with over 200 Poland-based specialists. Our expertise spans data architecture and sectoral specialization. We collaborate with tech partners like Microsoft, AWS, Google, Oracle, and Snowflake to implement cutting-edge solutions. We provide comprehensive support from strategy definition to solution implementation and development, covering all aspects of Data & Analytics.
THE WORK:
- Design, build, and operate scalable ELT/ETL pipelines using data from APIs, databases, event streams, and third-party systems
- Develop and maintain orchestration workflows in Apache Airflow with monitoring, observability, retries, and alerting
- Build and optimize data models in Snowflake and Databricks that power analytics, reporting, and AI applications
- Improve data quality through validation, testing, monitoring, and lineage
- Investigate production incidents, perform root-cause analysis, and implement long-term fixes
- Collaborate with analytics engineers, data scientists, product teams, and software engineers
- Contribute to engineering standards (testing, Git workflows, CI/CD, documentation, code reviews)
- Leverage AI coding tools (e.g., GitHub Copilot, Codex, Cursor) to accelerate development while maintaining quality
Flexible: The work location for this role may include a mix of working remotely (most of the time), onsite at a client or in an Accenture office - depending on specific project circumstances With all our roles, there is some in-person time for collaboration, learning and building relationships with clients, peers, leaders, and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.
THE WORK:
- Design, build, and operate scalable ELT/ETL pipelines using data from APIs, databases, event streams, and third-party systems
- Develop and maintain orchestration workflows in Apache Airflow with monitoring, observability, retries, and alerting
- Build and optimize data models in Snowflake and Databricks that power analytics, reporting, and AI applications
- Improve data quality through validation, testing, monitoring, and lineage
- Investigate production incidents, perform root-cause analysis, and implement long-term fixes
- Collaborate with analytics engineers, data scientists, product teams, and software engineers
- Contribute to engineering standards (testing, Git workflows, CI/CD, documentation, code reviews)
- Leverage AI coding tools (e.g., GitHub Copilot, Codex, Cursor) to accelerate development while maintaining quality
Flexible: The work location for this role may include a mix of working remotely (most of the time), onsite at a client or in an Accenture office - depending on specific project circumstances With all our roles, there is some in-person time for collaboration, learning and building relationships with clients, peers, leaders, and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.
🔍 Dekoder Ogłoszenia
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AI-Accelerated Development
Może oznaczać wykorzystanie narzędzi AI do wspomagania pracy, ale też potencjalnie większą presję na szybkość i efektywność.
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implement implement cutting-edge solutions
Może oznaczać pracę z nowymi technologiami, ale też potencjalnie brak stabilnych, sprawdzonych rozwiązań i częste eksperymenty.
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Flexible: The work location for this role may include a mix of working remotely (most of the time), onsite at a client or in an Accenture office - depending on specific project circumstances
Chociaż praca zdalna jest dominująca, istnieje możliwość pracy stacjonarnej u klienta lub w biurze, co może wymagać elastyczności i podróży.
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Investigate production incidents, perform root-cause analysis, and implement long-term fixes
Oznacza odpowiedzialność za rozwiązywanie problemów w środowisku produkcyjnym, co może być stresujące i czasochłonne.
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Contribute to engineering standards (testing, Git workflows, CI/CD, documentation, code reviews)
Wskazuje na zaangażowanie w procesy jakościowe i dobre praktyki, co jest pozytywne, ale może też oznaczać dodatkowe obowiązki poza bezpośrednim tworzeniem kodu.