Aplikuj teraz

Data Engineer

Huuuge Games Sp. z o.o.

Warszawa + 1 lokalizacja
13 500 - 20 000 zł/miesiąc
Hybrydowa
Umowa o pracę, Kontrakt B2B
Umowa o pracę
💼 Kontrakt B2B
🏠 Hybrydowa
Pełny etat

About the project

At Huuuge Games we make top grossing mobile games that bring people together through fun and social mobile gaming.

Become a part of an exciting adventure bringing fun & truly social experiences to millions of players around the world from one of our offices in Poland.

We are an in-office-first company and operate in a hybrid model (3 days from the office).

Join our Data Engineering team and be a crucial part of our data-driven engine. We're a group of curious and driven problem-solvers focused on transforming vast, complex datasets into clear, actionable insights. In this role, you'll be responsible for a large part of our data lifecycle - creating ETL pipelines, high-performance aggregate tables and dashboards. You'll partner directly with Analysts, Big Data Developers, and business stakeholders company-wide, enabling high-value projects. If you thrive on working with big data, love the challenge of turning raw information into polished, high-impact business knowledge, and want to leverage cutting-edge tools and techniques, we want to hear from you!

Your responsibilities

  • Design, build, and maintain robust ETL/ELT pipelines, transforming raw, disparate Big data inputs into high-quality, insightful structured tables and views.
  • Architect, create, and maintain the company's core KPI dashboards and reports ensuring accuracy and performance for mission-critical business tracking.
  • Integrate data from vast different sources—including product usage, marketing campaigns, and various third-party providers—to create a unified, holistic view of the business.
  • Partner closely with Data, Product, and Business teams to scope, design, and deploy advanced data solutions that solve complex challenges.
  • Drive high-standards development processes, actively contributing to CI/CD practices, and rigorous production deployment/monitoring to ensure pipeline reliability.
  • Perform research, analysis, and proof-of-concepts for new technologies and solutions, keeping our stack on the cutting edge.
  • Elevate team expertise by technically mentoring other team members and performing thorough code reviews.
  • Support downstream data teams, such as Analytics and Data Science, ensuring they have the reliable, clean data necessary to deliver actionable insights and maximize business value.

Our requirements

  • 3+ years of professional experience as a Data Engineer or BI Developer, ideally within a large-scale, Big Data environment.
  • 3+ years of hands-on experience in Scala and/or Python, with a strong preference for practical experience in the Apache Spark ecosystem (Spark Scala/PySpark).
  • Expert-level proficiency in SQL and demonstrable experience working with analytical database technologies (e.g., Databricks, Snowflake, BigQuery, Impala, Redshift).
  • Direct experience working with and publishing reports in data visualization tools like Tableau.
  • Proven experience in the design and development of complex data manipulation processes, including the creation of KPIs, analytical data aggregates, dashboards, and reports.
  • A firm understanding of the overall BI, analytics, and Big Data ecosystems.
  • Strong communication skills and the ability to work effectively and cross-functionally with business stakeholders in a fast-paced environment.
  • Fluency in English (written and verbal).
  • Experience handling and understanding data related to the gaming or mobile applications industry.
  • Extensive working knowledge of the Databricks environment, including proficiency with its advanced analytical or ML features.
  • Familiarity with mobile app marketing attribution or broader marketing-related data activities.
Wyświetlenia: 12
Opublikowanaokoło miesiąc temu
Wygasaza około 2 miesiące
Rodzaj umowyUmowa o pracę, Kontrakt B2B
Tryb pracyHybrydowa
Źródło
Logo

Podobne oferty, które mogą Cię zainteresować

Na podstawie "Data Engineer"