Senior AI Data, Analytics Engineer

Samsara

. Partner on defining the strategy and multi-quarter roadmap for MDA's data and AI foundation .

Posted 10/14/2026full-timeRemote • United StatesSenior💰 $137,445 - $231,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering and analytics, with a strong focus on building and managing data infrastructure, including ETL/ELT pipelines and data models. Proficient in Python and SQL, with experience in AI-enabled data products and cross-team collaboration to drive data-driven decision-making.

Highest-signal resume keywords

Expert-Level PythonExpert-Level SQLData ModelingETL/ELT ExperienceDatabricks Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringAnalytics EngineeringAI EngineeringData Warehouse ArchitectureLakehouse ArchitectureDBTSemantic Layer DesignAgentic Coding ToolsData VisualizationPredictive Analytics

Soft Skills

Cross-Team CollaborationMentoringProblem SolvingCommunicationLeadership

Tools & Technologies

DatabricksSnowflakeBigQuerySalesforceMarTech ToolsStreamlitClaude WorkflowsWeb Frameworks

Industry Keywords

Data InfrastructureBIKPIAI ProductsGTM TeamsData QualityData PipelinesConversational AnalyticsMarketing AnalyticsSales Analytics

Tech Stack

Tools & technologies

BigQueryETLPythonSQL

About the role

Key responsibilities & impact

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
Design semantic layers, data dictionaries, and structured documentation for self-serve BI and conversational analytics
Partner with the BI team to ensure sales and marketing KPIs use trusted, well-modeled data
Translate ambiguous business questions from Marketing, Sales, and R&D into clear requirements and scalable solutions
Lead complex, cross-team initiatives end to end, including new data pipelines and integrations
Manage risk across interdependent teams and own reliability and data quality
Serve as senior technical lead for complex problems, raising engineering quality and code review standards
Remove bottlenecks affecting multiple teams and mentor engineers and analysts
Build AI-enabled data products and agents with integrations, retrieval pipelines, and evaluation practices
Automate manual workflows with AI across Marketing and GTM teams from concept through production
Ship and review high-quality Python and SQL, including AI-generated work
Champion Samsara’s cultural principles across global teams and new offices

Requirements

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
Hands-on Databricks or similar platforms 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 and verification 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 and independently gathering requirements with technical and non-technical stakeholders
Experience supporting Marketing, Sales, or Product teams
Ideal: Experience with Databricks and AI Agents within the ecosystem
Ideal: Software engineering background beyond data or AI engineering
Ideal: Expertise in data visualization and dashboards for sales and marketing KPIs
Ideal: Familiarity with CRM such as Salesforce, marketing automation, web analytics, and MarTech tools
Ideal: Experience with Streamlit, Claude workflows, or web frameworks
Ideal: Data science, machine learning, or predictive analytics experience
Ideal: Comfort working in an exploratory environment and iterating on new data sources and methodologies
Must reside in the United States
Legal right to work at the company and in the specified work location, if applicable

Benefits

Comp & perks

Initial RSU grant with no vesting cliff
Ongoing equity refresh opportunities tied to performance
Performance-based bonus/variable pay
Flexible, employee-led remote model
Professional development stipend
Comprehensive health plans
Parental leave plans
Above-market total compensation opportunities
Flexible working model with remote, hybrid, or on-site options aligned to operational requirements