Samsara
Senior AI Data & Analytics Engineer II
$137K–$231K
Remote - CA +1 · Remote · Senior · Full-time · Posted Oct 14, 2026
- Location
- Remote - CA
Remote - SF Bay Area - Experience
- 8+ years in data engineering, analytics engineering, or AI engineering, including deep hands-on data engineering experience.
- Visa sponsorship
- Candidates must reside in the US; employment offers are contingent on the ability to secure and maintain the legal right to work at the company and in the specified work location.
About the job
Build and lead the marketing data and AI foundation, delivering reliable pipelines, models, semantic layers, and AI-enabled products for analytics and workflow automation.
What you'll do
- Set the strategy and roadmap for marketing data and AI, and architect its pipelines, Gold Layer tables, and data models.
- Enable self-service BI and conversational analytics through semantic layers, documentation, and trusted KPIs.
- Lead cross-team data initiatives and build, evaluate, and monitor AI agents and automated workflows.
What they ask for
- 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 Databricks or similar.
- Experience building semantic layers and structured documentation for AI ingestion and agentic workflows; experience shipping, evaluating, and monitoring production LLM or agent systems.
- Regular use of agentic coding tools, ownership and verification of AI-generated output, and a track record leading cross-team data initiatives and supporting Marketing, Sales, or Product teams.
Nice to have
- Databricks and AI Agents experience; software engineering background beyond data or AI engineering.
- Sales and marketing KPI dashboards; GTM systems, Streamlit or web frameworks, data science, machine learning, or predictive analytics experience.
Pay
$137,445 — $231,000 USD (annual base salary)
Tools
Python, SQL, DBT, Databricks, Snowflake, BigQuery, Claude Code, Cursor
AI focus
Build and operate AI-enabled data products and agents, including integrations, retrieval pipelines, evaluation and monitoring; automate Marketing and GTM workflows with AI and verify AI-generated code.
Model-written summary · the original posting is authoritative