Senior Marketing AI Data Engineer

Samsara is the pioneer of the Connected Operations™ Cloud, helping organizations harness IoT data to improve their operations. They are seeking a Senior Marketing AI Data Engineer to architect and maintain complex marketing databases and data infrastructure for AI/ML initiatives, enabling advanced segmentation, targeting, and analytics.

Responsibilities:

• Architect and maintain complex marketing databases, datasets, pipelines and Samsara’s Customer Data Platform (CDP) to enable advanced segmentation, targeting, automation and analytics
• Design and implement data infrastructure for AI/ML initiatives, including building pipelines for Generative AI applications, feature stores, and vector database integrations to support predictive modeling and personalization
• Support the execution of expanding conversational BI and Ambient AI within the marketing organization in partnership with the BI team
• Support in the automation of many manual tasks through the use of AI leading to efficiency gains for the whole marketing organization
• Manage critical, high-volume data pipelines to enable our growth initiatives and advanced analytics. Manage the SLAs for those data pipelines and constantly improve efficiency and data quality
• Facilitate sophisticated data integration and transformation requirements for moving data between applications; ensuring interoperability of applications with data mart, AI models, and CDP environments
• Autonomously partner directly with non-technical stakeholders (Marketing, Sales, Ops) to translate ambiguous business questions into technical requirements and scalable data solutions without needing constant supervision
• Write sophisticated yet optimized data transformations in Python/SQL to generate data products consumed by customer systems and Analytics, Marketing Operations, and Sales Operations teams
• Mentor junior engineers, conduct code reviews, and help define best practices for the data engineering team

Requirements:

• 5+ years of working experience in a data engineering or data engineering adjacent role
• Expert Python and SQL knowledge with strong hands-on data modeling experience
• Proven experience engineering data pipelines for AI/ML workloads (e.g., preparing unstructured data for LLMs, working with vector stores, or building feature engineering pipelines)
• Proven experience building and scaling RAG (Retrieval-Augmented Generation) infrastructure, including managing vector database integrations and data-to-embedding pipelines for LLM applications
• Deep experience with data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools
• Hands-on experience working with modern data technologies stack, such as Databricks, DBT, Google BigQuery, Redshift, RDS, Snowflake or similar solutions
• Demonstrated ability to lead requirement gathering sessions independently, bridging the gap between business needs and technical implementation
• Has demonstrated the ability to have exploratory conversations with stakeholders to understand further opportunities for automation across marketing
• Familiarity with customer, marketing and/or web data
• Experience integrating data from core Sales and Marketing platforms (e.g. Marketing Automation, CRM, and web analytics)
• Self-starter, motivated, responsible, innovative and technology-driven individual who performs well both independently and as a team member
• A proactive problem solver and have good communication as well as project management skills to relay your findings and solutions across technical and non-technical audiences
• Experience working with Databricks
• Knowledge of Marketo, Salesforce.com and Google Analytics
• Experience working with CDPs such as Hightouch, Segment, Lattice, Blueshift, Lytics or Adobe Real-time CDP
• Experience with data visualization tools and packages (e.g. Looker, Domo, Tableau, MixPanel)
• Familiarity with Marketing Technologies (MarTech stacks)
• Experience with MLOps principles and tools (e.g., MLflow, Kubeflow) and deploying models into production environments