Senior AI Data & Analytics Engineer – AI-Powered Pipelines

Samsara; Austin (CO); Remote; USD 137,000 - 231,000; Full time

Benefits offered by this job

RSU grant

Flexible working

Job summary

Samsara in the US is seeking an experienced data/AI engineer for the Marketing Data and Analytics (MDA) Engineering team. You will architect Databricks pipelines, Gold Layer tables, and semantic models to power segmentation, targeting, automation, and analytics.

You’ll design self-serve BI interfaces and AI-enabled data products, translate business questions into scalable data solutions, and drive cross-team initiatives while mentoring engineers and analysts.

Qualifications

• 8+ years of experience in data/AI engineering, including hands-on data engineering.
• Expert-level Python and SQL proficiency with strong data modeling experience.
• Deep experience with data warehouse/lakehouse architectures and the modern data stack (ETL/ELT).
• Experience building semantic layers and AI-ready data documentation.
• Experience shipping and evaluating LLM or agent systems in production; collaborating with Marketing/Sales/PM teams.

Responsibilities

• Define the strategy and multi-quarter roadmap for MDA's data and AI foundation.
• Architect and own Samsara's marketing data infrastructure and core data models.
• Design semantic layers and data dictionaries for AI ingestion and self-serve BI.
• Translate business questions into scalable data solutions with autonomous workstreams.
• Lead cross-team data initiatives end to end and mentor engineers/analysts.
• Drive AI-driven data products and agent-based solutions with reliable pipelines.

Skills

Python

SQL

Databricks

Data modeling

AI engineering

Tools

Snowflake

BigQuery

Job description

Samsara in the US is seeking an experienced data/AI engineer for the Marketing Data and Analytics (MDA) Engineering team. You will architect Databricks pipelines, Gold Layer tables, and semantic models to power segmentation, targeting, automation, and analytics.

You’ll design self-serve BI interfaces and AI-enabled data products, translate business questions into scalable data solutions, and drive cross-team initiatives while mentoring engineers and analysts.