Informacje o stanowisku

We are seeking a skilled Big Data Engineer to join our team and manage the processing of subscription data for various clients services, including Arcade, Music, TV+, and Fitness+. This role involves working with large-scale, shared datasets to support multiple teams, providing aggregated insights for machine learning (ML), data science (DS), and analytics functions. The ideal candidate will have experience in building and optimizing data pipelines, ensuring data integrity, and delivering actionable insights across departments.

This position involves working on a small team to develop large scale data pipelines and analytical solutions using Big Data technologies.

• 4+ years engineering experience with relevant tech stack
• Excellent  English to communicate with customer team directly
• Strong understanding of data warehousing concepts and big data technologies
• Ability to work in a fast-paced, dynamic environment
• Strong problem-solving skills and attention to detail

We are seeking a skilled Big Data Engineer to join our team and manage the processing of subscription data for various clients services, including Arcade, Music, TV+, and Fitness+. This role involves working with large-scale, shared datasets to support multiple teams, providing aggregated insights for machine learning (ML), data science (DS), and analytics functions. The ideal candidate will have experience in building and optimizing data pipelines, ensuring data integrity, and delivering actionable insights across departments.

This position involves working on a small team to develop large scale data pipelines and analytical solutions using Big Data technologies.

,[Writing Spark pipelines in Scala, Clickstream data, Maintaining existing pipelines, Implementing new features and utilizing common libraries / framework written in Scala, Working with Apache Superset Requirements: Scala, Spark, Apache, SQL, Airflow, Big data, Big Query, Linux/Unix, Interpersonal skills, Clickstream, AWS Tools: Jira, Agile, Scrum. Additionally: Sport subscription, Private healthcare, Flat structure, Small teams, International projects, In-house trainings, Team Events, Private health care, 5 additional sick leave days, Benefit platform, knowledge sharing environment, Free coffee, Bike parking, Free snacks, Free beverages, Modern office, Startup atmosphere, No dress code, Free breakfast, Kitchen, Play room, Shower.

Praca Warszawa

Warszawa - Oferty pracy w okolicznych lokalizacjach