Engineer

Netradyne harnesses the power of Computer Vision and Edge Computing to revolutionize the modern-day transportation ecosystem. We are a leader in fleet safety solutions. With growth exceeding 4x year over year, our solution is quickly being recognized as a significant disruptive technology. Our team is growing, and we need forward-thinking, uncompromising, competitive team members to continue to facilitate our growth.

About the Role

• Lead architecture and development of cloud data infrastructure supporting real-time health operations dashboards and telematics analytics
• Own the health operations dashboard platform—design real-time data aggregation, time-series analytics, and operational dashboards for internal teams
• Design and operate scalable data pipelines on Amazon EMR (Apache Spark/Scala) orchestrated with Apache Airflow for high-volume device telemetry processing
• Architect and operate production Apache Cassandra clusters for operational data and time-series workloads; optimize schema, compaction strategies, and replication for dashboard query performance
• Design streaming pipelines on Amazon Kinesis and Apache Flink for real-time health event processing, status aggregation, and operational alerting
• Own end-to-end data quality, schema governance, retention policies, and observability across ingestion, streaming, batch, and query layers
• Build highly available Java/Spring Boot services for health metric computation, data operations, and dashboard backends with idempotent consumers and fault handling
• Lead design reviews, mentor engineers, investigate production incidents, and drive technical strategy with Product, QA, DevOps, and partner teams

Required Qualifications

• 6-10 years hands-on backend engineering with deep expertise in Java, Spring, and Spring Boot
• Production experience with Apache Cassandra: data modeling, consistency tuning, compaction strategies, cluster operations, and troubleshooting
• Strong Apache Spark and Scala experience for distributed batch processing; proven ability to run Spark jobs on Amazon EMR with Apache Airflow
• Experience with streaming systems (Apache Flink or Kinesis): stream joins, windowing, aggregations, and operational latency optimization
• Strong PostgreSQL background and understanding of polyglot data architectures
• Experience with AWS data services: S3, EMR, RDS, Glue, Kinesis, SQS, IAM, CloudWatch
• Solid understanding of distributed systems: retries, idempotency, fault tolerance, eventual consistency
• Experience with real-time analytics systems or operational dashboards