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Third Wave Automation is a Series C-funded startup applying machine learning to materials handling, delivering autonomous forklift navigation and infrastructure-free pallet handling that adapts to changing warehouse environments. As Senior Data Engineer, you will be the architect of the company's data infrastructure and strategy, responsible for building the analytical foundation that drives decision-making across the organization.
You will have significant autonomy to challenge existing metrics and KPIs, determining what truly matters for measuring autonomous fleet performance. Your work will involve deep exploratory analysis of complex, real-world data generated from autonomous products operating in unpredictable customer environments—data that defies standard templates and requires creative problem-solving.
Key responsibilities include: auditing and evolving organizational KPIs; performing deep-dive analysis to uncover hidden signals in autonomous product data; designing and implementing novel data models that predict future performance in customer environments; and influencing the overall data architecture to support evolving organizational needs. You will engineer data ingestion pipelines, partner closely with Engineering and Product teams to inform requirements, work with Customer Success to provide reporting tools, and create compelling visualizations that translate complex data into clear narratives.
The role emphasizes first-principles thinking, statistical fluency with advanced techniques for non-linear datasets, and technical mastery in SQL, Python, or JavaScript with deep experience in data warehouses and analytics tools (BigQuery, Looker, Grafana, BigTable preferred). You should have database architect-level proficiency in design, data modeling, and data mining techniques. Beyond traditional analysis, you will deploy AI agents and automated workflows to expand alerting capabilities and bridge massive datasets with actionable insights. Strong presentation skills and ability to influence executives through data storytelling are essential.
Preferred qualifications include zero-to-one experience building data functions from scratch in startup environments, domain expertise in robotics, autonomous vehicles, IoT, or industrial automation, and deep experience with dbt and analytics engineering practices.
