Data Engineer

About the role

DroneShield is seeking a Data Engineer to join our team in Sydney, Australia. Reporting to the SensorFusionAI (SFAI) Team Lead, you will develop the core data pipelines and tools that turn real-world, multi-sensor data into actionable AI intelligence — powering systems that operate in the world's most complex and high-stakes environments.

This is a unique opportunity to apply your data engineering expertise in a deeply mission-driven company, working with diverse, high-volume, real-world sensor data (e.g., RF, optical, radar) in dynamic environments.

Responsibilities, Duties and Expectations 

• Design, develop, maintain and/or refine internal software tools used for processing data, workflow automation, benchmarking and testing the SensorFusionAI engine.
• Analyse real-world sensor data, identify critical parameters and plan data collection strategy ensuring our target classification models remain at the cutting edge.
• Lead data analysis during new sensor integrations, evaluating detection accuracy and their fit for use within our sensor fusion framework.
• Liaise with drone pilots, QA and field-service engineers to collect real-world data from our multi-sensor installations.
• Oversee data annotation processes and quality control to ensure consistent, model-ready datasets.
• Implement and maintain automated workflows and pipelines (e.g., Git, CI/CD, MLOps, DataOps) to uphold the highest performance and quality standards.
• Continuously improve data engineering pipelines to ensure performance, scalability, and reliability.
• Work in close collaboration with relevant stakeholders to troubleshoot and resolve bug/issue reports.
• Maintain a high standard of software quality through documentation, testing, and code reviews.
• Collaborate closely with other engineers and become a valued member of an autonomous, cross-functional team.

Qualifications, Experience and Skills 

• BS degree in Computer Science, Mathematics or similar technical field of study or equivalent practical experience
• Minimum 3 years of experience in a professional Software Engineering environment
• Strong background in data engineering
• Demonstrated experience in creating automated workflows (CI/CD, DataOps) and AI/ML pipelines (MLOps)
• Proficiency in an object-oriented programming language with strong expertise in one or more general purpose programming languages (ideally Python/Golang)
• Strong grasp of data structures, algorithms, and the application of mathematics and physics in software development
• Familiarity with Linux and containerisation

Nice to have

• Experience in AI or Machine Learning projects
• Proficiency in C++, meta build tools (CMake) and unit testing frameworks
• Experience developing data intensive real-time applications and/or GPU based processing systems (TensorRT, CUDA…)
• Knowledge of sensor fusion and object tracking algorithms

Who you are

• You have a strong foundation in software and data engineering, and you are confident in designing scalable systems that ingest, process, and transform large volumes of real-world sensor data. 
• You have hands-on experience building tools, pipelines, or frameworks that support AI/ML workflows. 
• You have worked across the entire data lifecycle — from raw ingestion and transformation to preparing clean, labeled datasets for model training and validation. 
• You have hands-on experience with CI/CD, containerization, and workflow orchestration tools, and enjoy automating complex processes for speed and reliability. 
• You take pride in delivering clean, well-documented, and tested code that integrates seamlessly with broader systems and is easy for others to maintain. 
• You are a self-driven learner, always seeking to improve and stay at the forefront of your field. 
• You are comfortable running your software in Linux environments. 
• You thrive in fast-paced, high-stakes settings and are motivated to help DroneShield scale globally. 

Note for recruitment agencies: We do not accept unsolicited candidates from external recruiters unless specifically instructed.