Senior Data Engineer II

About the Role As Apartment List's data platform grows across more domains, more pipelines, and more stakeholders, the architectural decisions made today determine how much technical debt we're paying down in a year. We're looking for a Senior Data Engineer II (IC4) to own that architecture; end-to-end pipeline design, platform investment tradeoffs, and the technical judgment calls that keep the system reliable as it scales. This is not a design-from-the-whiteboard role. You'll still be hands-on-keyboard: writing pipelines, debugging production issues, and shipping code alongside the team. What sets this role apart is scope; you'll make architectural decisions independently, influence how Analytics Engineering, Data Science, and Engineering partners build on the platform, and be the person other data engineers come to when a design decision needs a second opinion. You'll work closely with Analytics Engineering, Data Science, and Engineering partners to shape how the data platform evolves. Here's what you'll do as part of the team Own and evolve data pipeline architecture across core domains — ingestion, transformation, modeling, and serving — making project-level architectural decisions independently and evaluating tradeoffs between freshness, cost, scalability, and simplicity. Lead the design and implementation of platform-level improvements: warehouse cost management, co [... source excerpt omitted ...] ence) before they become blockers, and making the case for them. Drive large, technically complex projects or multiple concurrent medium-sized initiatives that span teams, taking responsibility for outcomes rather than just execution. Lead monitoring and testing strategy for your domain: proactively close observability gaps across the org, build alerting ahead of failures, and serve as the go-to engineer for the hardest production issues. Influence technical decisions and architectural direction beyond the Data & Analytics team, partnering directly with EPD stakeholders on infrastructure decisions that affect their roadmaps. Actively mentor other data engineers and analytics engin [... source excerpt omitted ...] g tooling and automation that creates leverage for the whole team, not just individual output, and coaching others on effective, validated use. Here are the skills and experience you'll need to be successful Must-haves: 7+ years of data engineering experience, including a demonstrated track record of owning end-to-end pipeline architecture, not just implementing to spec. Deep experience designing orchestration workflows in Apache Airflow, including making architectural tradeoffs across ingestion, transformation, modeling, and serving layers. Experience working with containerized data infrastructure in production, including deploying services, diagnosing operational issues,