Data engineer gcp/etl

2 tygodni temu


Warszawa, Mazovia, Polska PKO Bank Polski Pełny etat


Na co dzień w naszym zespole:
  • budujemy procesy zasilania operacyjnej składnicy danych,
  • projektujemy i realizujemy rozwiązania informatyczne w obszarze zasilania danych,
  • analizujemy dane oraz przygotowujemy dla nich modele logiczne i fizyczne,
  • stroimy zapytania SQL na bazie relacyjnych i hurtowianych w on-prem i na Chmurze GCP,
  • tworzymy przepływy off-linowe oraz strumieniowedanych,
  • przygotowujemydatamarty tematyczne na bazach relacyjnych i kolumnowych,
  • tworzymy koncepcje rozwiązań i implementacje rozwiązań w oparciu o wymagania i potrzeby biznesu,
  • usuwamy incydenty i bierzemy udział w rozwiązywaniu problemów,
  • wspieramy testy i wdrażania zmian w zakresie procesów zasilania danych,
  • pomagamy przy serwisowaniu wdrożonego oprogramowania,
  • tworzymy rozwiązania ładowania danych w Python,
  • pracujemy zgodnie z modelem DevOps.


To stanowisko może być Twoje, jeśli:
  • posiadasz doświadczenia jako develeoper Data Enegineer:
    • w obszarze procesów integracji danych za pomocą narzędzi ETLowych (Informaitica Power Center),
    • w obszarze technologii GCP (Big Query, Pub-Sub, Google Cloud Anthos, Cloud Storage Buckets,
    • w programowaniu w języku Phyton (znajomość jednego z framework Phyton: Flask, Django),
    • w projektowaniu i tworzeniu relacyjnych baz danych (PostgresSQL, Oracle),
  • pracujesz w środowisku chmurowym na Google Cloud Platform (Big Query, Cloud SQL, Kubernetes)
  • znasz środowisko Linux (doświadczenie w pracy z terminalem, podstawowa znajomość skryptów powłoki bash),
  • znasz narzędzie harmonogramujące: Apache Airflow,
  • masz doświadczenie w pracy z dużymi wolumenami danych ~100TB.
Dodatkowym atutem będzie znajomość:
  • Dash, Streamlit,
  • SqlAlchemy,
  • aplikacji uruchamianymi w kontenerach (Kubernetes, Anthos, Docker lub podobne,
  • aplikacji do harmonogramowania zadań ScheduleIN,
  • środowiska SAS,
  • aplikacji do raportowania i budowania dashboardów np. Google Data Studio, SuperSet,
  • narzędzi do monitorwania np. grafana,
  • rozwiązań chmurowych wykorzystywanych w procesach ładowania danych np.. data flow, nifi.


Miejsce pracy: Warszawa - praca hybrydowa

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