Senior AI Data & Analytics Engineer II

About the Role

As part of Samsara's Marketing Data and Analytics (MDA) Engineering team, you will shape the technical roadmap alongside BI and Data Science peers. You will architect core Databricks pipelines, Gold Layer tables, and semantic models, turning ambitious, ambiguous business challenges into high-value data products, autonomous agents, and cross-functional automation.

This role is open to candidates residing in the US.

Responsibilities

• Partner on defining the strategy and multi-quarter roadmap for MDA's data and AI foundation.
• Architect and own Samsara's marketing data infrastructure: ETL/ELT pipelines, Databricks Gold Layer tables, and the core data models powering segmentation, targeting, automation, and analytics.
• Design semantic layers, data dictionaries, and structured documentation that enable self-serve BI and conversational analytics, partnering with BI to ensure sales and marketing KPIs are built on trusted data.
• Translate ambiguous business questions from Marketing, Sales, and R&D into clear requirements and scalable solutions autonomously without dedicated PM support.
• Lead complex, cross-team initiatives end to end: stand up new data pipelines and integrations quickly, manage risk across interdependent teams, and own data quality and reliability.
• Serve as the senior technical lead: raise the bar for engineering quality and code review, remove bottlenecks, and mentor engineers and analysts.
• Drive the strategic use of AI to build AI-enabled data products and agents, including retrieval pipelines, integrations, and evaluation practices.
• Identify and automate manual workflows with AI across Marketing and GTM teams from prototype to production.
• Ship high-quality Python and SQL, directing agentic coding tools while verifying AI-generated output before production.
• Champion and embed Samsara’s cultural principles as the company scales globally.

Minimum Requirements

• 8+ years of experience in data engineering, analytics engineering, or AI engineering, including deep hands-on data engineering experience.
• Expert-level Python and SQL, with strong hands-on data modeling and dbt experience.
• Deep experience with data warehouse and lakehouse architectures, ETL/ELT, and the modern data stack, including hands-on Databricks (or similar, such as Snowflake or BigQuery).
• Experience building semantic layers and structured documentation optimized for AI ingestion and agentic workflows.
• Agentic coding tools (e.g., Claude Code, Cursor) as part of your regular workflow, with ownership of verifying AI-generated output.
• Experience building, shipping, evaluating, and monitoring LLM or agent systems in production.
• Track record of leading complex, cross-team data initiatives, including independent requirements gathering with technical and non-technical stakeholders.
• Experience supporting Marketing, Sales, or Product teams.

Preferred Qualifications

• Experience working with Databricks and building AI Agents within the ecosystem.
• Software engineering background beyond data or AI engineering.
• Expertise in data visualization and building dashboards for sales and marketing KPIs.
• Familiarity with go-to-market data and systems: CRM (e.g., Salesforce), marketing automation, web analytics, and MarTech tools.
• Experience building interactive applications with Streamlit, Claude workflows, or web frameworks.
• Data science, machine learning, or predictive analytics experience.
• Comfort working in an exploratory environment testing and iterating on new data sources.