Senior Data Analyst

About ATI:

Automated Tire (ATI) is on a mission to reinvent tire changing and wheel balancing using cutting-edge robotics. We are transforming a process that hasn’t fundamentally changed in decades into an automated, high-performance system built for the future of automotive service.

Founded by experienced entrepreneurs and backed by leading players across the automotive and tire industries, ATI is building technology that will redefine how cars are serviced. Our team combines deep robotics expertise with real world deployment, moving fast from prototype to production and scaling solutions directly in the field.

If you are excited by hands-on robotics, real-world impact, and the challenge of building category-defining technology from the ground up, ATI is the place to do the most meaningful work of your career.

Position Overview:

We are looking for a Senior Data Analyst to join our growing robotics startup. In this role, you will sit at the intersection of data engineering and analytics — translating complex, high-dimensional data from robotics and sensor systems into actionable insights that drive product strategy and operational excellence. You will partner closely with software engineers, ML engineers, product managers, and hardware teams to ensure that data is not only available and reliable, but deeply understood and put to use.

Responsibilities:

Data Analysis & Business Intelligence

• Serve as the primary analytical partner to business stakeholders — translating their questions and goals into metrics, frameworks, and insights that drive decisions across product, operations, and leadership.
• Translate complex, multi-source datasets (robotics telemetry, sensor streams, computer vision outputs) into actionable insights for both technical and non-technical audiences.
• Conduct analyses to identify trends, anomalies, and opportunities across the product stack — from edge device performance to model accuracy and fleet-level behavior.
• Define and track KPIs for product quality, model performance, data health, and operational efficiency.
• Design, build, and maintain interactive dashboards and reports (e.g., Tableau, Looker, Hex) that provide real-time visibility into business and product performance.

Analytics Engineering

• Define and own the analytical layer of the data and ML platform — building the data models, transformations, and pipelines that power reporting and insight delivery.
• Design, develop, and maintain self-serve analytics infrastructure: semantic layers, metrics catalogs, and reporting pipelines that empower the broader organization to answer their own questions.
• Partner with engineering to ensure dashboard data sources are reliable, performant, and aligned with defined data contracts and SLAs.
• Establish and document standards for the analytics layer, including naming conventions, metric definitions, refresh cadences, and access controls.

Data Quality & Observability

• Implement and champion data quality frameworks: automated validation, anomaly detection, SLA monitoring, and lineage tracking across all data sources.
• Implement robust observability: build dashboards, alerts, and metrics for pipeline performance, data drift, model health, and system reliability.
• Partner with engineering to define and enforce data contracts and schema standards across all upstream sources.

Cross-Functional Collaboration & Leadership

• Collaborate cross-functionally with product, hardware, and CV teams to align analytical decisions with product goals and user impact.
• Hire, mentor, and grow a world-class team of data and ML engineers; set technical standards and guide architectural decisions.

Shape the strategic roadmap for how ATI leverages data and AI to unlock new capabilities in robotics and physical intelligence

• Act as a data advocate — educating partners on best practices in data interpretation, statistical rigor, and decision-making under uncertainty.

Requirements

• 8+ years of experience in data analytics, data science, or related roles — with demonstrable impact on product or operational outcomes.
• Expert-level SQL skills: complex query writing, CTEs, window functions, data modeling, schema design, partitioning, and query optimization across large-scale datasets — with the ability to independently source and validate data without engineering support.
• Experience with BI and visualization tools (e.g., Tableau, Looker, Superset, or similar) and building self-serve analytics platforms.
• Experience with cloud infrastructure (AWS, GCP, Azure) and modern data ecosystems (data lakes, containers, serverless). 
• Excellent communication and collaboration skills; ability to translate technical constraints into product impact and convey complex findings to non-technical audiences.

Preferred Qualifications:

• Background in robotics, autonomous systems, SLAM, 3D perception, or sensor fusion.
• Familiarity with data lake architectures.
• Experience in closed-loop feedback systems, online learning, or real-time adaptation.