Serve Robotics builds and operates autonomous, geofenced sidewalk delivery robots and commercial on-demand delivery services, using edge AI (Nvidia Jetson) for onboard autonomy and an Uber Eats deployment agreement.
At Serve Robotics, we’re reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It’s designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses. The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We’re looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity. WHO WE ARE We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully. Responsibilities - Lead the Team: Lead, mentor, and grow a team of data and analytics engineers. This includes hiring, performance management, career development, planning, and setting technical standards. - Technical Leadership: Define the data engineering and analytics roadmap, aligned with company goals. This includes prioritizing data platform investments, reporting needs, analytics capabilities, and cross-functional data initiatives. - Data Platform Ownership: Oversee the design, reliability, scalability, and governance of the company’s data infrastructure, such as data warehouses, data lakes, ETL/ELT pipelines, orchestration systems, semantic layers, and BI tooling. - Analytics Delivery: Ensure business stakeholders have accurate dashboards, metrics, reporting, and ad hoc analysis to support decision-making across functions such as product, operations, finance, sales, marketing, and executive leadership. - Empowering Self-Service: Make self-service an organization-wide goal by building rich, trusted datasets and enabling access through AI-powered natural language interfaces. - Data Quality and Governance: Establish standards for data accuracy, lineage, documentation, access controls, privacy, security, and compliance. Qualifications - 6+ years of professional experience in data engineering and analytics including 2+ years experience leading teams of Sr. Data/Analytics Engineers. - Data leadership experience: Proven experience managing data engineering, analytics engineering, BI, or analytics teams, including hiring, coaching, performance management, and roadmap planning. - Strong technical foundation: Deep understanding of data warehouses, data lakes, ETL/ELT pipelines, orchestration, data modeling, BI platforms, semantic layers, and data quality practices. - Experience with modern data stacks: Hands-on experience with tools such as Snowflake, BigQuery, Redshift, Databricks, dbt, Airflow, Fivetran, Looker, Tableau, Power BI, or similar platforms. - Cross-functional, business-oriented partnership: Strong track record partnering with executives and teams across product, operations, finance, engineering, sales and marketing, translating business goals into data strategy, dashboards and analytics products that improve decision-making. - AI-powered self-service analytics experience: Demonstrated ability to build trusted, governed data products and enable organization-wide access through natural language or AI-powered analytics interfaces, with strong controls for accuracy, security, privacy, compliance and usability. - Data governance expertise: Experience establishing standards for data quality, documentation, access controls, privacy, security, auditability, metric definitions, and trusted data products, including SOX, SOC2 compliance and compliance with international data policies and regulations (e.g., GDPR, data residency requirements). - Education or equivalent experience: Bachelor’s degree in computer science, data science, engineering, statistics, mathematics, information systems, or a related field. Advanced degrees are a plus. *Please note: The listed base salary range applies to candidates based in the US. Compensation may vary depending on location, experience, and role alignment. We are open to qualified candidates working remotely in Canada - Canada - ALL: $179,976 - CAD- $221,828 CAD