Senior Manager, Data & Analytics Engineering

Responsibilities

• Own the end-to-end technical roadmap for Data & Analytics Engineering, from ingestion and pipeline architecture through the modeling layer and the tables and metrics stakeholders rely on.
• Directly manage and develop Analytics Engineers and Data Engineers, including hiring, coaching, growth, and performance management.
• Make and defend platform and architecture investment cases covering orchestration, warehouse cost, CI/CD, data access, and tooling.
• Set and uphold standards for testing, monitoring, documentation, and code quality.
• Serve as the escalation point for complex architectural and production issues.
• Partner with Product, Data Science, Marketing, and other stakeholders to translate ambiguous data needs into a scoped, sequenced roadmap.
• Communicate technical tradeoffs to technical and non-technical audiences.
• Represent team priorities, risks, and investment needs in cross-functional and leadership planning.

Requirements

• Direct management experience for data engineers and/or analytics engineers, including hiring, coaching, and performance management.
• Experience leading end-to-end data production, from platform through analytics marts.
• Hands-on data infrastructure experience, including pipeline orchestration, warehousing, and platform reliability architecture.
• Hands-on SQL-based modeling experience sufficient to evaluate modeling and metrics decisions.
• Experience setting technical roadmaps and making investment cases to leadership.
• Ability to evaluate and communicate architectural and modeling tradeoffs, such as freshness versus cost and scalability versus simplicity.
• Experience partnering with non-technical stakeholders to define metrics and resolve conflicting data priorities.

Nice-to-haves

• Experience managing both data engineering and analytics engineering functions.
• Experience owning a BI or semantic-layer tool such as Looker or Tableau as a product.
• Experience establishing cross-team data model standards.
• Experience introducing AI-assisted tooling into engineering or analytics workflows.
• Experience with marketplace, real estate, subscription, or performance marketing data models.

Compensation and Benefits

• US total target compensation: $171,000–$208,000 in Zone 3, $187,000–$226,000 in Zone 2, or $202,000–$245,000 in Zone 1, including equity.
• Base salary ranges: $150,000–$177,000 in Zone 3, $164,000–$192,000 in Zone 2, or $177,000–$208,000 in Zone 1.
• Pre-IPO stock options and other financial compensation, where applicable.
• Medical, dental, and vision coverage with premiums covered for employees and dependents.
• Unlimited flexible time off, company holidays, recharge days, and a holiday break.
• Home office, health and wellness, parental and family leave, fertility, and family-forming reimbursements or benefits.
• 401(k) plan.
• Team events, mentorship, training, and career development opportunities.
• Strategic initiatives with meaningful impact and visibility.