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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 ExperienceDatabricks Experience
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 ArchitectureAgentic Coding ToolsBuilding Semantic LayersData Quality ManagementRequirements GatheringData Visualization
Soft Skills
MentoringCross-Team CollaborationProblem SolvingOwnershipCommunication
Tools & Technologies
DatabricksSnowflakeBigQueryDBTSalesforceMarTech ToolsStreamlitClaude WorkflowsWeb FrameworksConversational Analytics
Industry Keywords
Data InfrastructureAI ProductsMarketing KPIsSales KPIsGTM TeamsExploratory EnvironmentPredictive AnalyticsMachine LearningData PipelinesDocumentation
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 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, code reviews, engineering quality, and bottleneck removal
- 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 high-quality Python and SQL, increasingly directing agentic coding tools
- Review and verify AI-generated work before production
- Champion Samsara’s cultural principles while scaling globally and across 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
- Ability to verify and take ownership 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
- 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
Benefits
Comp & perks- Initial RSU grant with no vesting cliff
- Ongoing RSU 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
- Above-market total compensation opportunities
- Remote work support where aligned with operational requirements
- Offices available for employees who prefer to work in-person
- Reasonable accommodations throughout the recruiting process