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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 ArchitectureSemantic Layer DesignStructured DocumentationAgentic Coding ToolsLLM SystemsRequirements Gathering
Soft Skills
Cross-Team CollaborationMentoringRisk ManagementProblem SolvingCommunication
Tools & Technologies
DatabricksSnowflakeBigQueryDBTAI-Enabled Data Products
Industry Keywords
Data InfrastructureBusiness IntelligenceMarketing DataSales KPIsGTM Teams
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 pipelines and integrations
- Manage risk across interdependent teams and own reliability and data quality
- Serve as senior technical lead, raise engineering and code-review quality, remove bottlenecks, 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 high-quality Python and SQL, increasingly directing agentic coding tools
- Review and verify AI-generated work before production
- Champion Samsara’s cultural principles as the company scales 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, 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 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
- In-person office option
- Equal opportunity employment
- Reasonable accommodations throughout the recruiting process