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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data engineering and analytics, with a strong focus on Python, SQL, and data modeling. Capable of leading cross-team initiatives and building AI-enabled data products while ensuring data quality and reliability.
Highest-signal resume keywords
Expert-Level PythonExpert-Level SQLData ModelingETL/ELT PipelinesDatabricks
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringAnalytics EngineeringAI EngineeringData Warehouse ArchitectureLakehouse ArchitectureDBTSemantic Layer DesignAgentic Coding ToolsLLM SystemsData Quality Assurance
Soft Skills
Cross-Team CollaborationIndependent Requirements GatheringMentoring
Tools & Technologies
DatabricksSnowflakeBigQuerySalesforceStreamlitClaude CodeCursor
Industry Keywords
Marketing Data InfrastructureBusiness IntelligenceSales KPIsGTM WorkflowsMarTech ToolsPredictive AnalyticsExploratory Data Work
Tech Stack
Tools & technologiesBigQueryETLPythonSQL
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 requirements and scalable solutions
- Lead complex, cross-team initiatives from end to end, including new data pipelines and integrations
- Own reliability and data quality of delivered systems
- Serve as senior technical lead for complex problems, code review, engineering quality, and mentoring
- Build AI-enabled data products and agents with integrations, retrieval pipelines, and evaluation practices
- Automate manual Marketing and GTM workflows with AI from prototype through production
- Ship and review high-quality Python and SQL, including AI-generated code
- Champion Samsara’s cultural principles across the organization
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
- Independent requirements gathering with technical and non-technical stakeholders
- Experience supporting Marketing, Sales, or Product teams
- Preferred: experience with Databricks and AI Agents, software engineering beyond data or AI engineering, data visualization and sales/marketing KPI dashboards, CRM such as Salesforce, marketing automation, web analytics, MarTech tools, Streamlit, Claude workflows, web frameworks, data science, machine learning, predictive analytics, and exploratory data work
Benefits
Comp & perks- Initial RSU grant with no vesting cliff
- Ongoing refresh opportunities tied to performance
- Performance-based bonus/variable pay
- Equity for eligible roles
- Flexible, employee-led remote model
- Professional development stipend
- Comprehensive health plans
- Parental leave plans
- Flexible working model
- Remote work support where aligned with operational requirements