Data Engineer

📋 Description

• Design, develop, and optimize large-scale data apps with Scala, Spark, Java.
• Build and maintain high-performance data pipelines processing 80–90 million records daily.
• Develop and integrate Native APIs and data services for business-critical apps.
• Collaborate with cross-functional teams to deliver robust data solutions.
• Optimize Spark jobs and data workflows for high throughput and low latency.
• Implement best practices for data quality, monitoring, governance, and operations.

🎯 Requirements

• Strong hands-on experience in Scala, Spark, and Java.
• Built large-scale distributed data systems handling tens of millions daily.
• Develop and consume Native APIs and microservices.
• Deep understanding of Spark architecture, tuning, partitioning, caching.
• ETL/ELT and large batch/streaming pipelines experience.
• Distributed systems, concurrency, and high-volume data knowledge.

🎁 Benefits

• Open, inclusive culture
• No forced hierarchy; growth opportunities
• Career advancement and global impact