Senior Manager, Data & Analytics Engineering
$187,000–$226,000 year
RemoteUnited States
Job Summary
Own the end-to-end technical roadmap for Data & Analytics Engineering, managing pipeline architecture, modeling layers, and platform investments from ingestion through to the analytics mart. Directly lead Analytics and Data Engineering teams, handling hiring, performance management, and technical tradeoffs on orchestration, warehousing, and CI/CD. Partner with Product, Data Science, and Marketing to translate ambiguous needs into sequenced roadmaps, defending investment cases and upholding standards for testing, monitoring, and code quality. Serve as the escalation point for complex architectural issues while communicating freshness, cost, and scalability decisions to both technical and non-technical stakeholders.
Required Qualifications
- Experience directly managing data engineers and/or analytics engineers, including hiring, coaching, and performance management.
- Experience leading end to end data production, from platform to analytics mart.
- Hands-on data infrastructure experience: designing or making architectural tradeoffs in pipeline orchestration, warehousing, and platform reliability, deep enough to review others' architecture decisions and make the final call.
- Hands-on experience with SQL-based modeling sufficient to evaluate modeling and metrics decisions, not just pipeline and platform work.
- A track record of setting technical roadmaps and making an investment case to leadership, not just executing against a roadmap set by someone else.
- Demonstrated ability to evaluate and communicate architectural and modeling tradeoffs (freshness vs. cost, scalability vs. simplicity) to both technical and non-technical stakeholders.
- Experience partnering with non-technical stakeholders to define metrics and resolve conflicting data priorities across teams.
Desired Qualifications
- Experience managing both a data engineering and an analytics engineering function specifically, rather than one or the other.
- Experience owning a BI/semantic layer tool (Looker, Tableau, or similar) as a product, including cross-team data model standards.
- Experience introducing AI-assisted tooling into engineering or analytics workflows at a team level.
- Background in marketplace, real estate, subscription, or performance marketing data models.
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