Manager, Analytics Engineering, Data & AI Foundations

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $154.8k - $247.7k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Analytics Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 0%

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HubSpot

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2006

🤝 B2B

☁️ SaaS

📣 Marketing

B2B • SaaS • Marketing

HubSpot is an AI-powered customer platform that combines marketing, sales, and customer service software into one integrated suite. With over 238,000 customers in 135 countries, HubSpot offers tools for marketing automation, sales management, customer service, content marketing, operations, and B2B commerce. With products like Marketing Hub, Sales Hub, Service Hub, and Content Hub, HubSpot enables businesses to generate leads, close deals, and provide excellent customer support, all while using AI to enhance operations and insights. The platform is designed to unify teams and customer data, supporting both small startups and large enterprises in their growth journey.

📋 Description

• Lead and develop a team of Analytics Engineers, supporting career growth, hiring, retention, feedback, and priority alignment • Set the team's vision and operating model, translating Operations and Analytics Engineering goals into a focused roadmap and success measures • Partner with Analytics Engineering managers to improve composable agents, semantic models, shared data assets, and developer tooling • Collaborate with analysts and analytics committees to incorporate feedback into platform strategy and delivery • Review architecture and implementation approaches with technical leaders and establish scalable, robust, practical, reusable standards • Prioritize cross-functional initiatives, defining objectives, sequencing, responsibilities, and resource allocation • Partner with AI Readiness delivery teams to deploy implementation resources and remove execution blockers • Own and evolve core platform assets, Analytics Engineering tooling, reusable patterns, and automation • Advance the composable agentic Analytics Engineering delivery system and support responsible AI-assisted workflow adoption • Guide development of semantic models and metric layers for analytics and AI consumption • Establish standards for data modeling, testing, code review, documentation, observability, reliability, and cost management • Build enablement programs and cross-functional partnerships for modern tools and practices, while contributing hands-on when needed

🎯 Requirements

• Experience leading and developing Analytics Engineers or similar technical data professionals, including hiring, coaching, performance management, and career development • Demonstrated ability to define a vision and translate it into a practical strategy, roadmap, and operating model • Strong understanding of analysts' workflows and shared data assets, tooling, and standards • Strong proficiency with SQL, data modeling, ETL, ELT, Snowflake, dbt, and Looker • Hands-on dbt experience, including scalable modeling patterns, testing, macros, and development workflows • Experience building or managing shared data platform assets, developer toolkits, internal frameworks, semantic models, or metric layers • Experience with AI-assisted development and agentic workflows, such as Claude Code, composable skill-based systems, AI agents, or MCP integrations • Track record of leading complex, cross-functional data initiatives from ambiguity through production • Experience driving change and adoption across a large or complex organization • Strong prioritization and project management skills • DevOps mindset characterized by automation, collaboration, continuous improvement, reliability, and frequent iteration • Strong communication skills and ability to distill technical decisions, trade-offs, and strategy into clear business terms • Experience working with globally distributed teams and version control tools such as GitHub Enterprise Cloud • Python is a plus, but not required

🏖️ Benefits

• Flexible work arrangements, including Remote or Office options • In-person onboarding at a regional HubSpot office for Engineering team members • In-person Product Group Summit and other gatherings for broader Product team members • Alternative arrangements available for travel limitations or other reasons • Disability accommodations and assistance • AI-assisted candidate screening with human hiring decisions • Global team and office environment • Award-winning company culture