Senior AI Data & Analytics Engineer II

Samsara•Seattle, WA

About The Position

Samsara is hiring a Senior AI Data & Analytics Engineer II for its Marketing Data and Analytics (MDA) Engineering team. The role will shape the technical roadmap for the team's data and AI foundation in partnership with BI and Data Science peers. The engineer will architect Databricks pipelines, Gold Layer tables, semantic models, and data products that power marketing segmentation, targeting, automation, analytics, and self-serve BI. The role also focuses on building reliable AI-enabled products and agents, and translating ambiguous business challenges into scalable solutions. Candidates must reside in the US. This senior technical role leads complex, cross-team initiatives from requirements gathering through delivery, with responsibility for data quality, reliability, engineering standards, and mentoring. It also drives AI-based workflow automation across Marketing and go-to-market teams, using Python, SQL, and agentic coding tools while verifying AI-generated work before production. The role partners with Marketing, Sales, R&D, BI, and other stakeholders and contributes to Samsara’s cultural principles as the company scales.

Requirements

At least 8 years of experience in data engineering, analytics engineering, or AI engineering, including deep hands-on data engineering experience.
Expert-level Python and SQL skills, 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 a similar platform such as Snowflake or BigQuery.
Experience building semantic layers and structured documentation optimized for AI ingestion and agentic workflows.
Regular use of agentic coding tools such as Claude Code or Cursor, with ownership of and verification of AI-generated output.
Experience building, shipping, evaluating, and monitoring LLM or agent systems in production.
A track record of leading complex, cross-team data initiatives, including independently gathering requirements from technical and non-technical stakeholders.
Experience supporting Marketing, Sales, or Product teams.

Nice To Haves

Experience working with Databricks and building AI agents within its ecosystem.
Software engineering experience beyond data or AI engineering, including turning ambiguous, unfamiliar problems into well-architected solutions and delivering them.
Expertise in data visualization and building dashboards for sales and marketing KPIs.
Familiarity with go-to-market data and systems, including CRM systems such as 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 and testing and iterating on new data sources and methodologies.

Responsibilities

Partner on defining the strategy and multi-quarter roadmap for MDA’s data and AI foundation.
Architect and own marketing data infrastructure, including ETL/ELT pipelines, Databricks Gold Layer tables, and core data models for segmentation, targeting, automation, and analytics.
Design semantic layers, data dictionaries, and structured documentation that enable self-serve BI and conversational analytics.
Partner with the BI team to ensure sales and marketing KPIs are based on trusted, well-modeled data.
Translate ambiguous business questions from Marketing, Sales, and R&D into clear requirements and scalable solutions, working autonomously and influencing decisions with data and sound reasoning.
Lead complex, cross-team initiatives end to end, including standing up data pipelines and integrations, managing risks across interdependent teams, and owning reliability and data quality.
Serve as senior technical lead for difficult problems, raise engineering and code-review standards, remove cross-team bottlenecks, and mentor engineers and analysts.
Build AI-enabled data products and agents, including integrations and retrieval pipelines, and establish evaluation practices to ensure reliability and trustworthiness.
Identify and automate manual workflows with AI across Marketing and GTM teams, taking ideas from concept through prototype to production and influencing organizational roadmaps.
Ship high-quality Python and SQL, increasingly by directing agentic coding tools, and review and verify AI-generated work before production.
Champion and model Samsara’s cultural principles: Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, and Win as a Team.