Overview
Senior AI Data & Analytics Engineer II on Samsara's Marketing Data and Analytics (MDA) Engineering team, building the data and AI foundation for marketing, sales and GTM teams.
What you'll do
- Partner on defining the strategy and multi-quarter roadmap for MDA's data and AI foundation.
- Architect and own marketing data infrastructure: ETL/ELT pipelines, Databricks Gold Layer tables, and core data models that power segmentation, targeting, automation and analytics.
- Design semantic layers, data dictionaries and structured documentation that enable self-serve BI and conversational analytics, partnering with the BI team on trusted sales and marketing KPIs.
- Translate ambiguous business questions from Marketing, Sales and R&D into clear requirements and scalable solutions, working autonomously without dedicated PM support.
- Lead complex, cross-team initiatives end to end, including standing up new data pipelines and integrations, managing risk across interdependent teams, and owning reliability and data quality.
- Serve as senior technical lead for the team's hardest problems: raise the bar for engineering quality and code review, remove bottlenecks, and mentor engineers and analysts.
- Build AI-enabled data products and agents, with integrations, retrieval pipelines and evaluation practices that keep them reliable and trustworthy.
- Identify and automate manual workflows with AI across Marketing and GTM teams, taking ideas from concept to prototype to production.
- Ship high-quality Python and SQL, increasingly by directing agentic coding tools, and review and verify AI-generated work before production.
What you'll need
- 8+ years of experience in data engineering, analytics engineering, or AI engineering, including deep hands-on data engineering experience.
- Expert-level Python and SQL.
- 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) are part of your regular workflow, and you verify and take ownership of 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.
Nice to have
- Experience working with Databricks and building AI Agents within the ecosystem.
- Software engineering background beyond data or AI engineering, with a track record of turning ambiguous, unfamiliar problems into well-architected, delivered solutions.
- 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.
Details
- Open to candidates residing in the US.
- Annual base salary range: $137,445 to $231,000 USD, plus eligibility for an initial RSU grant and refresh opportunities.
Read the full description and apply on the company’s own careers page.