Senior Data Platform Engineer — Architect & Mentor

Openkrill; United States; Remote; USD 189,000 - 255,000; Full time

Job summary

Apartment List is seeking a Senior Data Engineer II to own data pipeline architecture across ingestion, transformation, modeling and serving, balancing data freshness, cost, scalability and simplicity. You will be hands-on, shipping code and debugging production issues, while shaping how Analytics Engineering, Data Science and Engineering partners build on the platform.

This role emphasizes architectural autonomy, cross-team collaboration, reliability, and the thoughtful integration of AI

Qualifications

• 7+ years of data engineering with end-to-end pipeline ownership.
• Deep Airflow experience including tradeoffs across layers.
• Production containerized infra deployment and troubleshooting.
• Ability to communicate architectural tradeoffs to varied stakeholders.
• Experience building/advancing CI/CD for data pipelines.
• Led incident response and monitoring strategies.
• Influenced cross-team technical decisions and mentoring.

Responsibilities

• Own and evolve data pipeline architecture across core domains with independent decisions.
• Design platform-level improvements: cost, compute, access control, reliability.
• Lead initiatives that improve platform health (CI/CD, data access, developer exp).
• Drive large, complex projects spanning teams and outcomes.
• Lead monitoring strategy and close observability gaps; pre-empt failures.
• Influence decisions beyond Data & Analytics; partner with stakeholders.
• Mentor other data engineers and analytics engineers; review designs.
• Integrate AI into workflows and build automation for the team.

Skills

End-to-end pipeline architecture

Airflow orchestration

Containerized production infra

CI/CD for data pipelines

Incident response & monitoring

Influence across teams

Mentoring data engineers

Tools

Datadog

Kubernetes

Job description

Apartment List is seeking a Senior Data Engineer II to own data pipeline architecture across ingestion, transformation, modeling and serving, balancing data freshness, cost, scalability and simplicity. You will be hands-on, shipping code and debugging production issues, while shaping how Analytics Engineering, Data Science and Engineering partners build on the platform.

This role emphasizes architectural autonomy, cross-team collaboration, reliability, and the thoughtful integration of AI