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.

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 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, ensuring core sales and marketing KPIs are built on trusted, well-modeled data.
• Translate ambiguous business questions from Marketing, Sales, and R&D into clear requirements and scalable solutions autonomously.
• Lead complex, cross-team initiatives end-to-end, managing risk across interdependent teams and owning reliability and data quality.
• Serve as 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 solve high-impact problems: build AI-enabled data products and agents, including integrations, retrieval pipelines, and evaluation practices.
• Identify and automate manual workflows with AI across Marketing and GTM teams.
• Ship high-quality Python and SQL, directing agentic coding tools and holding a high bar for verifying AI-generated output.

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 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 and methodologies.