Senior Data Engineer

About Netradyne:

Netradyne provides AI-powered technologies for fleet management and safer roads. An award-winning industry leader in fleet safety and video telematics solutions, Netradyne empowers thousands of commercial fleet customers across North America, Europe, and Asia to enhance their driver performance, reduce risk, and optimize operations.

Netradyne sets the standard among transportation technology companies for enhancing and sustaining road safety, with an industry-leading 25+ billion miles vision-analyzed for risk and an industry-first driver scoring system that reinforces safe behaviors. Founded in 2015, Netradyne is headquartered in San Diego with offices in San Francisco, Nashville, the UK and Bangalore. For more details visit: www.netradyne.com

Job Overview:

Job Overview: As a Senior Data Engineer at Netradyne, you will build and scale data platforms that power real-time AI and ML systems at the core of our fleet safety products. You will design and operate high-throughput streaming pipelines and production-grade data systems deployed at large scale, working closely with Data Science and ML teams to bring AI solutions to life in a fast-paced, impact-driven environment.

Key Responsibilities:

• Build and maintain scalable data pipelines for real-time and batch processing 
  (Kinesis, SQS-based systems).
• Develop data platforms supporting ML workflows including feature generation, 
  training, and validation pipelines.
• Optimize pipeline performance, reliability, and scalability across high-volume 
  environments.
• Develop backend components and services for data processing systems.
• Deploy, monitor, and troubleshoot production data systems.
• Work with distributed systems in containerized environments (Docker, 
  Kubernetes/EKS).
• Collaborate with Data Science and ML teams to productionise AI solutions.
• Follow engineering best practices including code quality, testing, and CI/CD 
  pipelines (Jenkins).
• Work with AI agents to solve data engineering problems at hand

Mandatory Skills:

• Bachelor’s degree in computer science or related field.
• Bachelor's/Master's degree in Computer Science or related field.
• 3–6 years of experience in Python-based data/backend engineering.
• Strong programming fundamentals — data structures, algorithms, and OOP.
• Experience with AWS services (Kinesis, SQS, Lambda, or similar).
• Experience building and managing data pipelines and workflows (Airflow/DAGs).
• Good understanding of data modelling and databases (RDBMS/NoSQL).
• Experience with Docker and Kubernetes.
• Hands-on experience with GitHub and CI/CD tools like Jenkins.
• Strong Linux fundamentals and debugging skills.
• Go