AI Data Analytics Engineer

Position: Staff AI Data Analytics Engineer
Who we areWith its A.I.

-powered robotic technology platform, Symbotic is changing the way consumer goods move through the supply chain. Intelligent software orchestrates advanced robots in a high-density, end-to-end system – reinventing warehouse automation for increased efficiency, speed and flexibility.

What we need

We are looking for an AI Analytics Engineer to join Symbotic. Your job will be to design and build an intelligent analytics ecosystem that aggregates operations data across multiple systems and leverages agentic AI to generate insights, dashboards, and proactive recommendations for executive leadership. This individual will play a critical role in enabling scalable, real-time visibility into business performance as we grow globally, with a focus on hands-on development of robust, production-level data systems and dashboards.

The ideal candidate brings broad exposure to different areas of a business and is comfortable moving across functions, asking questions, challenging assumptions, and proactively seeking out the information needed to solve ambiguous problems.

What you’ll do Business Analysis & Strategic Insights Partner with leaders and cross-functional teams to understand business questions, reporting needs, risks, and opportunities.

Work across different areas of the organization and develop an understanding of how business functions, processes, metrics, and data connect.

Analyze data to identify trends, risks, inefficiencies, and performance gaps, then translate findings into clear recommendations and next steps.

Proactively seek out answers, challenge assumptions when appropriate, and navigate ambiguity across different layers of the business.

Present your insights to C-suite level leaders to influence their strategy and operation thinking.

Data Consumption & Analytics Work with data engineering and platform teams to understand and consume data from existing enterprise data sources.

Understand database and schema structures, relationships between datasets, metric definitions, and how information flows across systems.

Use SQL and Python to query, analyze, transform, and work with data for custom analytics and reporting use cases.

Partner with teams responsible for data pipelines and infrastructure to communicate data requirements and resolve gaps or quality issues.

Reporting, Dashboards & Data Exploration Build custom dashboards and executive-ready reporting that clearly communicate KPIs, trends, risks, and business performance.

Use visualization and analytics tools such as Tableau, Power BI, Qlik, Looker, or similar platforms where appropriate.

Develop custom analytics experiences using Python, SQL, and other tools when traditional BI platforms are not sufficient.

Build mechanisms that allow users to search, query, drill into, and explore underlying data, including self-service and natural-language experiences where appropriate.

Ensure reporting is intuitive, actionable, and aligned with the decisions business leaders need to make.

AI-Enabled Analytics & Reporting Build on top of existing LLMs, agents, and enterprise AI capabilities to make analytics and reporting more effective.

Develop plugins, tools, integrations, search capabilities, and other reusable assets that extend existing AI platforms.

Use AI to automate or enhance data analysis, reporting, summarization, insight generation, and information retrieval.

Data Quality, Metrics & Governance Establish and enforce enterprise-wide data governance and standards, including clear ownership of core metrics across systems, metric definitions, calculation methodologies, source-of-truth alignment across systems.

Lead data governance and data quality efforts, including identifying and remediating inconsistencies across data sources and pipelines, and ensuring accuracy, consistency, and trust in analytics outputs.

What you’ll need Bachelor’s degree or higher in Computer Science, Data Science, Engineering, Mathematics, Business Analytics, Information Systems, or a related discipline.

Minimum of 8 years of experience in data analytics, analytics engineering, data science, business intelligence, business analytics, or a related field.

Strong business…