Data Engineer – Automotive Computer Vision Solutions

About the Position

We are seeking a brilliant, experienced Data Engineer to join our elite team. This is not just a backend role; it is an opportunity to join a tight-knit team where your impact is visible and immediate. You will build the data infrastructure that powers our validation engines and AI R&D breakthroughs. Working with datasets derived from real-world driving with top-tier car brands, you will enable the next generation of AI-based driver monitoring systems.

If you are looking for a place where quality matters, the culture is supportive yet ambitious, and the technology is cutting-edge — this is the place for you.

Responsibilities

• Own the Data Architecture

Design, build, and maintain our data warehouse, including scalable data pipelines for the ingestion, storage, and processing of both structured and unstructured datasets (images, video, and telemetry) from our global in-car data collection campaigns.

• Drive R&D Success

Develop and optimize data architectures that directly support the Algorithm team’s research and the D&V team’s validation activities.

• Automation & Tooling
• Develop automated ETL/ELT workflows to ensure frictionless access to “ground truth” datasets and regulatory validation datasets (including NCAP‑driven requirements).
• Create internal tools (CLI or UI-based) to streamline data retrieval, annotation, and quality assurance.
• Guarantee Quality

Implement data‑quality controls, integrity checks, lineage tracking, and dataset versioning aligned with automotive-grade rigor.

Ensure compliance with internal and external (OEM, regulatory) standards.

• Technical Leadership

Act as a solution architect within the D&V team, building technical bridges between our local algorithm experts and global product teams.

Guide the organization on data infrastructure advancements, cloud best practices, and scalable compute strategies.

What Are We Looking For

Must-Haves

• BSc in Computer Science, Electrical Engineering, experienced practical engineering or related technical field.
• 3+ years of hands-on Data Engineering experience in complex HW/SW environments
• Strong Python and SQL proficiency; experience building production-grade ETLs in Linux
• Deep understanding of CI/CD, Git, and modern software engineering workflows.
• Experience with AWS data tools, and orchestration frameworks (ex: Airflow, boto3, Lambda).
• Demonstrated experience working with unstructured data (ex: video/image pipelines).
• Hands-on experience integrating with sensors, embedded devices, or automotive hardware.
• Fluent English for collaboration with our global teams.

Strong Advantages

• Experience building data tools using Qt or similar UI frameworks.
• Familiar with Automotive, AI, or Computer Vision product ecosystems.
• Experience maintaining local or cloud-based model-training workflows (incl. Synthetic Data generation pipelines).
• Familiarity with large-scale annotation workflows, ground-truth management, or validation systems.

Personal Qualities

• Highly collaborative, thrives in a small and high-performing team.
• Strong analytical mindset with strong attention to details and a bias for automation and efficiency.
• A true team player who thrives in a small, high-quality team environment and contributes to our unique culture.