Sr. Business Intelligence and Insights Engineer

Third Wave Automation
Union City, Ca $131k – $216kPosted 26 March 2026

Job Description

Company Description Third Wave Automation is a rapidly growing startup that has demonstrated its core technology components, proven its market fit, and just closed its Series C funding. If you are excited about cutting edge machine learning, robotics that affects the real world, and want to join a company where your skills can have a huge impact, you’ll fit right in. Third Wave Automation is applying modern machine learning to materials handling—delivering site-specific forklift navigation and infrastructure-free pallet handling that continuously adapts to changing floor configuration and warehouse demand. Job Description Most data roles are about maintaining what already exists. This isn’t one of them. As our dedicated Business Intelligence Engineer, you aren't just joining a team; you are the architect of our data truth. We operate autonomous products in complex, unpredictable customer environments. This generates "messy" real-world data that defies standard templates. We need a skeptic and a creator—someone who looks at a dashboard and asks, "What are we missing?" and then builds the model to find it. How You Can Make an Impact You will have the autonomy to tear down existing models and build new ways to measure the performance of our autonomous fleet products in the real world. Challenge the Status Quo: Audit and evolve our organizational KPIs. If a metric isn't driving a decision, you’ll be the one to kill it and propose a better way to measure success. Deep-Dive Discovery: Go beyond the surface. Perform deep-dive exploratory analysis to find the "hidden" signals in our autonomous product data that others might overlook. Model Innovation: Design and implement novel data models that don't just track what happened, but leverage simulation models to predict what will happen next in our customer environments. Architecture Influence: Influence the design and support the documentation of the overall data structures to support the evolving needs of the organization. What You'll Do (Your First 90 Days and Beyond) Engineer the Pipeline: Provide critical feedback on our data ingestion pipelines and validate the data sources used for performance reporting. Partner for Growth: Build strong partnerships with Engineering and Product teams to inform solution requirements and influence the roadmap based on your findings. Empower Customers: Work with our Customer Success team to provide tools and reporting that give our customers a clear view into the value we provide. Visualize the Future: Create compelling visualizations for both internal and external consumption that translate complex data clusters into a clear narrative. Scale with an AI-First Mindset: Champion the use of generative AI tools (e.g., Gemini, Cursor) to automate the mundane and generate quality insights Qualifications First-Principles Thinking: You should be more interested in the "why" than the "how" and have a demonstrated ability to think from the ground up. Statistical Fluency: 7+ years of experience using advanced statistical techniques to analyze custom, non-linear data sets. Technical Mastery: Proficiency in SQL, Python, or Javascript, with deep experience in data warehouses and analytics tools (BigQuery, Looker, GrafanaBigTable preferred). Database Architect Mindset: Technical proficiency in database design development, data models, and techniques for data mining and segmentation. AI-Enabled Scale: Beyond traditional analysis, you have an appetite for deploying AI agents and automated workflows to expand our alerting surface area. You see AI not as a buzzword, but as a tool to bridge the gap between massive datasets and actionable insights. Master Storyteller: Excellent presentation skills with the ability to influence executives and engineering leads by turning data into a compelling story. Preferred Zero-to-One Experience: Proven track record of being the first data hire or building a data function from scratch in a sta ... (truncated, view full listing at source)
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