Big Data Engineer

Role Overview

Join a global, collaborative engineering environment where data is at the core of decision-making and product innovation. Design and maintain scalable data pipelines that enable reliable access to large volumes of structured and unstructured data.

What You Will Do

Design, build, and maintain scalable data pipelines and ETL processes, collaborate with data scientists and analysts, develop and implement data models, ensure data quality and integrity, and monitor and troubleshoot data systems.

Why It Might Be a Fit

This is a highly technical and impact-driven role within a distributed, international team where engineering excellence and continuous improvement are strongly valued. You will have the opportunity to work with modern cloud and big data technologies and participate in impactful projects involving large-scale data ecosystems.

Requirements

• Proven experience as a Big Data Engineer or Data Engineer in production environments
• Strong experience with Google Cloud Platform (GCP) and big data processing frameworks such as Apache Spark
• Solid programming skills in at least one language such as Python, Java, or Scala
• Strong knowledge of SQL and experience with relational databases such as MySQL or PostgreSQL
• Experience in data modeling, database design principles, and data architecture
• Familiarity with ETL tools, workflows, and data integration processes
• Understanding of data warehousing concepts and distributed data systems
• Strong analytical and problem-solving skills with high attention to detail
• Ability to work independently as well as collaboratively in international, cross-functional teams
• Strong communication skills in English (conversational level required for global collaboration)

Benefits

• Competitive salary aligned with experience and market standards
• Opportunity to work in a global, multicultural engineering environment
• Remote or hybrid flexibility depending on project requirements
• Exposure to modern cloud-based data engineering technologies and large-scale systems
• Continuous learning and professional development opportunities
• Collaborative and innovation-driven work culture
• Participation in impactful projects involving large-scale data ecosystems