Senior AI Data & Analytics Engineer II

Role overview Shape the data and AI foundation that supports marketing analytics, automation, and self-service insights. You’ll set technical direction with BI and data science partners, turn loosely defined business questions into dependable data products, and lead complex work across teams. The role combines hands-on engineering with technical leadership, mentoring, and careful application of AI.

Responsibilities - Help define the multi-quarter strategy and roadmap for data and AI capabilities. - Build and own ETL/ELT pipelines, Databricks Gold Layer tables, and models for segmentation, targeting, automation, and analytics. - Create semantic layers, data dictionaries, and documentation that enable trusted self-service and conversational analytics. - Translate needs from marketing, sales, and research teams into scalable technical solutions, working independently where needed. - Lead cross-team initiatives from new integrations through delivery, managing dependencies and owning reliability and data quality. - Raise engineering standards through technical leadership, code review, mentorship, and removal of delivery bottlenecks. - Develop AI-enabled data products and agents, including integrations, retrieval pipelines, and evaluation practices; automate manual workflows through production-ready prototypes.

Requirements - This is a senior technical leadership role requiring the ability to guide architecture, deliver complex cross-functional initiatives, and mentor engineers or analysts. - Strong Python and SQL skills, including the ability to review and verify code produced with AI-assisted development tools. - Experience designing and operating data pipelines, data models, and analytics foundations at scale. - Ability to turn ambiguous business needs into clear requirements and sound, maintainable solutions. - Strong judgment around data reliability, quality, and trustworthy AI-enabled systems.

Benefits and work setup - Open to candidates residing in the United States. - Flexible work model, with in-person, hybrid, or remote arrangements depending on role requirements. - Health and parental leave benefits and a professional development stipend.