Senior AI Data Engineer

Date PostedAugust 12, 2026LocationCanadaCompanySamsara Inc.Salary$119,000—$154,000 CADTypeSenior Level

Job Summary

Marketing Data and Analytics (MDA) is seeking a Senior AI Data Engineer to design, build, and operate production AI systems, agent orchestration, and marketing data infrastructure. This role involves turning ambiguous business problems into data products, AI agents, and automated workflows while partnering with cross-functional teams. Candidates should have extensive experience in data engineering, Python, SQL, and production LLM systems.

Responsibilities

  • Design and operate production AI systems and agent orchestration
  • Architect and maintain marketing databases, pipelines, and CDP
  • Identify and automate manual workflows using AI and data products
  • Partner with cross-functional stakeholders to define technical requirements
  • Ship high-quality Python and SQL code and conduct code reviews

Required Skills

  • 5+ years in data or AI engineering
  • Expert Python and SQL knowledge
  • Experience building LLMs/agents in production
  • Data warehouse architectures and modern data stack (Databricks, DBT, Snowflake, BigQuery)
  • Strong communication and autonomous project management skills

Job Details

About the role: Marketing Data and Analytics (MDA) is an integral team within Marketing. Our mission is to strengthen revenue performance by providing marketing and sales teams with the insights, tools, infrastructure, and consultation to make data-driven decisions. This role sits on MDA's Engineering team, working alongside our BI and Data Science teams. We are a scrappy, fast-moving team that takes ambiguous business problems and turns them into data products, AI agents, and automation, all while architecting and maintaining the data infrastructure that powers Samsara's marketing. This role is for someone who thinks on their feet, moves fast, and is comfortable owning problems end to end. This role is open to candidates residing in Canada. In this role, you will: - Design, build, and operate production AI systems, including agent orchestration, tool and API integrations, retrieval pipelines, and the evaluation harnesses that keep them reliable and trustworthy. - Architect and maintain marketing databases, datasets, pipelines, and Samsara's Customer Data Platform (CDP) to enable advanced segmentation, targeting, automation, and analytics. - Partner with the BI team to expand conversational analytics across the marketing organization. - Identify and automate manual workflows with AI, taking ideas from concept to prototype to a credible path to production, and delivering efficiency gains across marketing and go-to-market teams. - Stand up new data pipelines end to end, often for a tool that was onboarded yesterday: discovering the schema, working with partners inside Samsara and at the vendor, getting the data processed, and integrating it into our downstream systems. - Own the reliability and data quality of what you build. - Autonomously partner with technical and non-technical stakeholders (Marketing, Sales, R&D, and more) to translate ambiguous business questions into technical requirements and scalable solutions, without dedicated PM support. - Ship high-quality Python and SQL, increasingly by directing agentic coding tools, while holding a high bar for reviewing and verifying AI-generated work before it reaches production. - Mentor engineers, conduct code reviews, and help define best practices for the team. Minimum requirements for the role: - 5+ years of working experience in a data engineering or AI engineering role, including meaningful hands-on data engineering experience. - Expert Python and SQL knowledge with strong hands-on data modeling experience. - You have built and shipped systems that use LLMs or agents in production as part of your job. - Agentic coding tools (e.g., Claude Code, Cursor) are part of your regular workflow. - You actively seek out new ways to use AI to accelerate your work, and you verify and take ownership of AI-generated output. - Deep experience with data warehouse architectures, ETL/ELT, and the modern data stack (e.g., Databricks, DBT, Snowflake, BigQuery, or similar). - Demonstrated ability to lead requirements gathering independently, bridging the gap between business needs and technical implementation, and to spot opportunities for automation through exploratory conversations with stakeholders. - A self-starter who performs well independently and as a team member, with strong communication and project management skills across technical and non-technical audiences.