Senior Manager, Data & Analytics Engineering

Apartment List•Remote within the US,

2d•$171,000 - $245,000

About The Position

Apartment List is the premier rental matchmaker, connecting ready-to-move renters with compatible city properties. Our renters benefit from cutting-edge technology and a personalized approach when we match them with curated properties that fit their wishlist. Meanwhile, our supply partners harness our generative AI and machine learning to efficiently connect with our qualified renters. With performance-based pricing, our partners' success is our success as we strive to deliver renters a home they love at the value they deserve. Apartment List's data platform and the analytics built on top of it have grown up as two closely related but separately-run disciplines: one team owns the pipelines and infrastructure that get data in, the other owns the models and metrics that turn it into something the company can act on. This role exists to unify that work under one leader who is accountable for the full path from raw data to trusted table: pipeline architecture, platform investment, and the modeling and metrics layer stakeholders actually use. You'll manage the Analytics Engineering and Data Engineering teams directly, set the technical roadmap for both, and be the first line of judgment on architecture, tooling, and platform tradeoffs. This is a hands-in-the-work leadership role: you'll review pipeline and modeling decisions, not just project plans, and it's built to grow: as the combined function scales, so does the scope of this role.

Requirements

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.

Nice To Haves

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.

Responsibilities

Own the end-to-end technical roadmap for Data & Analytics Engineering, from ingestion and pipeline architecture through to the modeling layer and the tables and metrics stakeholders rely on, and prioritize it against real business need.
Directly manage and develop Analytics Engineers and Data Engineers, setting clear expectations, running regular 1:1s, and owning hiring, growth, and performance decisions for both disciplines.
Make and defend the case for platform and architecture investments (orchestration, warehouse cost, CI/CD, data access, tooling) before they become blockers
Set and uphold standards for testing, monitoring, documentation, and code quality, and be the escalation point for the hardest architectural or production issues.
Partner directly with Product, Data Science, Marketing, and other business stakeholders to translate ambiguous data needs into a scoped, sequenced roadmap, and communicate tradeoffs clearly to technical and non-technical audiences alike.
Represent the team's priorities, risks, and investment needs in cross-functional and leadership planning.