Senior Data Engineer

Company Description Humyn Labs is the research engine and data platform powering Physical AI, building the foundation for safe and effective human–robot coexistence. The company translates real-world human experience across sound, sight, motion, and touch into model-ready training data for frontier AI, robotics, and large language models. Its densely labeled, research-backed datasets are delivered as multimodal or fused signals tailored to specific model needs. Humyn Labs collects high-fidelity data across Latin America, Southeast Asia, the Middle East, and South Asia, including over 1M hours of egocentric video and 50K hours of audio in 36 languages to accelerate deployment-ready robotics. Humyn Labs is a member of the NVIDIA Inception program, reinforcing its focus on cutting-edge AI innovation.
Role Description This is a full-time, on-site Senior Data Engineer role based in Bengaluru. The Senior Data Engineer will design, build, and maintain scalable data pipelines to ingest, transform, and serve multimodal datasets (video, audio, motion, and other signals) for AI and robotics research. Responsibilities include developing data models and warehousing solutions, optimizing ETL workflows, and ensuring data quality, reliability, and performance across large, distributed datasets. The role involves close collaboration with data scientists, machine learning engineers, and research teams to understand data needs and translate them into robust, production-grade data infrastructure. The Senior Data Engineer will also contribute to architecture decisions, implement best practices in data governance and security, and help mentor other team members on modern data engineering standards.
Qualifications
Strong data engineering skills, including experience designing and implementing scalable data pipelines and distributed data processing solutions.
Proficiency in data modeling and data warehousing concepts to design efficient, well-structured schemas and analytical data stores.
Hands-on experience with Extract Transform Load (ETL) processes, including building, orchestrating, and monitoring ETL workflows in production.
Ability to apply data analytics skills to support experimentation, instrumentation, and performance insights across large, complex datasets.
Proficiency in modern data engineering tools and languages (e.g., Python, SQL, Spark, Kafka, Airflow, cloud data platforms).
Experience working with large-scale, multimodal or streaming data (e.g., video, audio, sensor data) is highly beneficial.
Knowledge of best practices in data security, privacy, governance, and observability for production data systems.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience.
Ability to collaborate effectively in cross-functional teams and communicate clearly with technical and non-technical stakeholders
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Work arrangement
No