Spark / Data Lakehouse Developer

Upvanta • Custom Software Development • IT Staffing & Staff Augmentation • Python • SQL • 5 days ago
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Salary
≈ $50k – $89k per year (Estimated)
Location
Hybrid (Wrocław, Poland)
Employment
Contractor

First seen by Alion on Oct 21, 2026.

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Upvanta

Upvanta is a Polish technology company that combines software development services with recruitment, supplying engineers and delivery teams to clients in Poland and western Europe. It works on custom application development, cloud and infrastructure engineering, data platforms and quality assurance, staffing those projects both from its own bench and through placements sourced for the client directly. The company is based in Warsaw, advertises a continuous board of technology vacancies under its own name, and works across financial services, retail and industrial accounts.
upvanta.com • HQ: Warsaw, Poland • IT Staffing & Staff Augmentation • Custom Software Development • 51-200 employees • Est. 2018

Kogo szukamy?

 

Do zespołu Data Platform szukamy doświadczonego Spark / Data Lakehouse Developera, który będzie rozwijał rozwiązania Data Engineeringowe związane z rekoncyliacją danych, MongoDB oraz architekturą Data Lakehouse.

 

Oczekiwania

  • min. 4 lata doświadczenia z Apache Spark,

  • bardzo dobra znajomość PySpark i Spark SQL,

  • doświadczenie z MongoDB i MongoDB Spark Connector,

  • praktyczna znajomość Apache Iceberg,

  • doświadczenie w budowie warstw Data Lakehouse: raw/bronze/silver/gold,

  • znajomość CI/CD i Jenkins,

  • znajomość Prometheus i Grafana,

  • doświadczenie w Scrum/Kanban oraz pracy z Jira/Confluence.

Wymagania

  • umiejętność optymalizacji procesów Spark,

  • doświadczenie w rekoncyliacji i kontroli jakości danych,

  • znajomość partitioningu, caching, broadcast joins i AQE,

  • doświadczenie w pracy z dużymi zbiorami danych,

  • samodzielność i analityczne podejście do rozwiązywania problemów,

  • umiejętność współpracy z zespołami Data, QA i DevOps.

Oferujemy

  • pracę przy nowoczesnej platformie Data Lakehouse,

  • udział w ciekawych projektach związanych z dużymi zbiorami danych,

  • pracę z nowoczesnym stackiem: Spark, MongoDB, Iceberg, Kubernetes, Prometheus, Grafana,

  • możliwość rozwoju i wpływu na rozwiązania technologiczne,

  • współpracę z doświadczonym zespołem,

 

Tech stack

  • Apache Spark
  • PySpark
  • Spark
  • SQL
  • MongoDB
  • MongoDB Spark Connector
  • Apache Iceberg
  • CI/CD
  • Jenkins
  • Prometheus
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