Senior AI Data & Analytics Engineer II

Samsara•Chicago, IL

About The Position

Samsara is hiring a Senior AI Data & Analytics Engineer II for its Marketing Data and Analytics 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 and own marketing data infrastructure, including Databricks pipelines, Gold Layer tables, core data models, semantic layers, and structured documentation that power analytics, segmentation, targeting, automation, and conversational analytics. The position translates ambiguous business challenges from Marketing, Sales, and R&D into scalable data products and AI-enabled solutions. It leads complex cross-functional initiatives end to end, owns reliability and data quality, and serves as a senior technical lead who raises engineering standards, removes bottlenecks, and mentors engineers and analysts. The role also builds and evaluates AI products and agents, automates manual workflows across Marketing and GTM, and uses agentic coding tools while taking responsibility for reviewing and verifying their output. Candidates must reside in the US.

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 responsibility for verifying and owning AI-generated output.
Experience building, shipping, evaluating, and monitoring LLM or agent systems in production.
A track record leading complex cross-team data initiatives, including independently gathering requirements from technical and non-technical stakeholders.
Experience supporting Marketing, Sales, or Product teams.
Must reside in the United States.

Nice To Haves

Experience working with Databricks and building AI agents within its 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, including CRM 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 the Marketing Data and Analytics team’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 to support self-serve BI and conversational analytics; partner with BI to build trusted sales and marketing KPIs.
Translate ambiguous business questions from Marketing, Sales, and R&D into requirements and scalable solutions, working autonomously and influencing decisions with data and sound reasoning.
Lead complex cross-team initiatives end to end, including launching pipelines and integrations, managing risks across dependent teams, and owning reliability and data quality.
Act as the senior technical lead for challenging 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, retrieval pipelines, and evaluation practices to ensure reliability and trustworthiness.
Identify and automate manual workflows with AI across Marketing and GTM, taking ideas from concept through prototype to production and influencing organizational roadmaps.
Deliver high-quality Python and SQL, increasingly by directing agentic coding tools, and review and verify AI-generated work before production.
Champion Samsara’s cultural principles: Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, and Win as a Team.