Data Engineer

The Data Engineering department is responsible for the full-stack design and development of Plarium’s central data platforms and business data services. The team builds cloud-based, large-scale data systems, including real-time streaming and ETL pipelines, that process massive volumes of data and support key business areas such as games & product design, marketing, retention, and monetization. These high-impact platforms play a critical role in driving the company’s overall business performance.

Responsibilities

• Lead data solutions, technical design, and hands-on development for Plarium’s data platform
• Data Platform: Build and optimize data platforms, applications, and pipelines for batch and real-time processing of massive (Petabytes) datasets in Python and SQL
• Build production-grade data services and components, with strong software engineering standards
• Microservices Development: Own, Design, implement, deploy, and maintain scalable
• Develop and optimize data models and SQL queries for high-volume analytical workloads
• Own data workflows end-to-end: development, deployment, monitoring, and performance optimization
• Front-end: Development using React and Next.js

What we expect

• Advanced SQL expertise (4+ years) - Proven ability to design and optimize efficient, low-latency SQL queries for modern cloud data warehouses (e.g. BigQuery).
• Data-intensive systems experience (4+ years) - Hands-on experience building, maintaining, and scaling data-heavy systems in production environments.
• Strong Python development (4+ years) - Experience writing production-grade Python for data processing, orchestration, and automation.
• ETL / Data Pipelines at scale - Proven experience developing and operating ETL pipelines using distributed processing frameworks (e.g., PySpark).
• Cloud & distributed systems - Experience designing and operating large-scale, distributed systems in cloud environments (GCP is a strong advantage).
• Data architecture fundamentals - Solid understanding of data modeling, data quality principles, and scalable system design.
• Production & deployment focus - Hands-on experience with CI/CD pipelines and deploying, operating, and maintaining production systems end-to-end. CI/CD pipelines and deploying

Our technology stack

• Notebook solutions (Databricks, Jupyter)
• Frontend development experience (React, Next.js)
• Streaming systems (Kafka, Spark Structured Streaming)
• BI & visualization tools (Qlik Sense / Looker / Tableau)