Engineer, Java & Spark

Overview

Hybrid Engineer role focused on building and modernizing cloud-based data solutions using Java and Apache Spark.

What you'll do

• Translate technology roadmaps into scalable, production-ready data solutions for cloud migration.
• Design, develop, and maintain high-performance batch and real-time data pipelines with Java and Apache Spark.
• Identify and resolve data processing bottlenecks and optimize query performance.
• Collaborate with architects, project leads, and product teams to align deliverables with priorities.
• Develop well-tested code, participate in code reviews, and contribute to technical documentation and best practices.
• Implement CI/CD pipelines, automated testing frameworks, and Infrastructure as Code standards.
• Mentor peers and share technical expertise.

What you'll need

• 3+ years in software or data engineering.
• Experience designing, developing, and supporting large-scale, production-grade data processing applications.
• Strong distributed systems and big data knowledge, including Apache Spark and Hadoop.
• Experience designing and deploying data solutions on AWS or GCP.
• Advanced proficiency in developing scalable, high-performance multithreaded Java applications.
• Hands-on experience with distributed data processing and large-scale analytics workloads using Apache Spark and Hadoop.
• Working knowledge of AWS or GCP data services, storage platforms, and cloud-native architectures.

Details

• Hybrid work mode with regular responsibilities both virtually and in-person at an assigned office location for at least two days per week.