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.

Benefits

Full time employees receive a competitive total compensation package along with employee-led remote and flexible working, health benefits, and much, much more.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

PythonSQLdata modelingdata pipelinesAI/ML workloadsRAG infrastructuredata warehouse architecturesETLELTdata transformations

Soft skills

communicationproject managementproblem solvingmentoringindependencecollaborationrequirement gatheringstakeholder engagementinnovationresponsibility