Manager, Analytics Engineering, Data & AI Foundations

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead and nurture a team of Analytics Engineers, fostering career development, hiring, employee retention, feedback, and alignment of priorities.

• Define the team's vision and operational framework, converting Operations and Analytics Engineering objectives into a coherent roadmap and success criteria.

• Collaborate with Analytics Engineering managers to enhance composable agents, semantic models, shared data resources, and developer tools.

• Work together with analysts and analytics committees to integrate feedback into platform strategies and delivery processes.

• Evaluate architecture and implementation strategies with technical leaders, establishing scalable, robust, practical, and reusable standards.

• Prioritize cross-functional projects, outlining objectives, sequencing tasks, assigning responsibilities, and allocating resources.

• Collaborate with AI Readiness delivery teams to roll out implementation resources and eliminate execution obstacles.

• Oversee and develop core platform resources, Analytics Engineering tools, reusable patterns, and automation processes.

• Advance the composable agentic Analytics Engineering delivery framework and encourage responsible adoption of AI-assisted workflows.

• Steer the development of semantic models and metric layers for analytics and AI utilization.

• Set standards for data modeling, testing, code reviews, documentation, observability, reliability, and cost management.

• Create enablement programs and cultivate cross-functional collaborations for modern tools and practices, contributing hands-on when necessary.

⛳️ Requirements

• Proven experience in leading and developing Analytics Engineers or similar technical data professionals, including responsibilities for hiring, coaching, performance management, and career progression.

• Demonstrated capability to articulate a vision and translate it into a feasible strategy, roadmap, and operational model.

• Strong understanding of analysts' workflows alongside shared data resources, tools, and standards.

• High proficiency in SQL, data modeling, ETL, ELT, Snowflake, dbt, and Looker.

• Hands-on experience with dbt, including scalable modeling patterns, testing, macros, and development workflows.

• Experience in building or managing shared data platform resources, developer toolkits, internal frameworks, semantic models, or metric layers.

• Familiarity with AI-assisted development and agentic workflows, such as Claude Code, composable skill-based systems, AI agents, or MCP integrations.

• Proven track record of leading intricate, cross-functional data initiatives from inception to production.

• Experience in driving change and fostering adoption across large or complex organizations.

• Strong prioritization and project management capabilities.

• DevOps mentality characterized by automation, collaboration, continuous improvement, reliability, and frequent iteration.

• Exceptional communication skills with the ability to translate technical decisions, trade-offs, and strategy into clear business language.

• Experience collaborating with globally distributed teams and utilizing version control tools such as GitHub Enterprise Cloud.

• Proficiency in Python is a plus but not mandatory.

🏝️ Benefits

• Flexible work arrangements, offering both Remote and Office options.

• In-person onboarding at a regional HubSpot office for Engineering team members.

• Participation in an in-person Product Group Summit and other gatherings for the broader Product team.

• Alternative arrangements available for travel restrictions or other considerations.

• Disability accommodations and assistance provided.

• AI-assisted candidate screening complemented by human hiring decisions.

• A global team and office environment.

• An award-winning company culture.