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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. Proven ability to lead cross-team initiatives and build AI-enabled data products while ensuring data quality and reliability.
Highest-signal resume keywords
Expert-Level PythonExpert-Level SQLData ModelingETL/ELT ExperienceDatabricks Experience
Tech Stack
Tools & technologiesAbout 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 end to end, including data pipelines and integrations
- Manage risk across interdependent teams and own reliability and data quality
- Serve as senior technical lead for complex problems, code review, 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 by directing agentic coding tools
- Review and verify AI-generated work before production
- Champion and embed Samsara’s cultural principles
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
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
- Offices available for employees who prefer to work in-person
- Reasonable accommodations throughout the recruiting process
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 ArchitectureSemantic Layer DevelopmentDBT ExperienceAgentic Coding ToolsLLM Systems MonitoringRequirements Gathering
Soft Skills
MentoringCross-Team CollaborationProblem SolvingRisk ManagementCommunication
Tools & Technologies
DatabricksSnowflakeBigQueryETL ToolsBI Tools
Industry Keywords
Data InfrastructureMarketing DataSales KPIsConversational AnalyticsAI-Enabled Products