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Salary: USD 189,000 - 229,000 / annual
Apartment List is seeking a Senior Data Engineer II (IC4) to own the architecture and evolution of its data platform as it scales across more domains, pipelines, and stakeholders. This is a hands-on role where you'll make architectural decisions independently while still writing pipelines, debugging production issues, and shipping code alongside the team.
Key Responsibilities:
- Own and evolve data pipeline architecture across core domains (ingestion, transformation, modeling, serving), making project-level architectural decisions independently and evaluating tradeoffs between freshness, cost, scalability, and simplicity.
- Lead design and implementation of platform-level improvements including warehouse cost management, compute efficiency, and access control architecture, treating reliability, observability, and cost efficiency as core design constraints.
- Identify and lead technical initiatives that improve platform long-term health, proactively surfacing investments in orchestration, CI/CD, data access, and developer experience before they become blockers.
- Drive large, technically complex projects or multiple concurrent medium-sized initiatives spanning teams, taking responsibility for outcomes.
- Lead monitoring and testing strategy for your domain, proactively closing observability gaps, building alerting ahead of failures, and serving as the go-to engineer for hardest production issues.
- Influence technical decisions and architectural direction beyond Data & Analytics, partnering directly with Engineering, Product, and Data Science stakeholders on infrastructure decisions.
- Actively mentor other data engineers and analytics engineers, reviewing architectural and modeling decisions, and operate as a technical peer to senior engineers across teams.
- Integrate AI meaningfully into data engineering workflows, building tooling and automation that creates leverage for the whole team and coaching others on effective, validated use.
Requirements:
Must-haves:
- 7+ years of data engineering experience with 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, and contributing to platform reliability and scalability.
- Demonstrated ability to evaluate and communicate architectural tradeoffs (freshness vs. cost, scalability vs. simplicity) to both technical and non-technical stakeholders.
- Experience building or significantly improving CI/CD practices for data pipelines, including automated testing, validation, and deployment.
- Track record of leading incident response and monitoring strategy for a domain, including building alerting and observability ahead of failures.
- Experience influencing technical decisions across multiple teams or functions, including partnering with engineering, product, or data science stakeholders outside immediate team.
- Experience mentoring other data engineers, including reviewing architectural and modeling decisions.
Nice-to-haves:
- Experience with Kubernetes-based data infrastructure.
- Experience leading a legacy ETL-to-modern-orchestration migration end-to-end.
- Familiarity with observability and monitoring tooling such as Datadog at platform-wide scale.
- Experience building internal tooling or automation (including AI-assisted) that other engineers rely on.
