Senior Data Engineer II

Responsibilities

• Own and evolve data pipeline architecture across ingestion, transformation, modeling, and serving layers.
• Make architectural decisions independently, evaluating tradeoffs among freshness, cost, scalability, and simplicity.
• Lead platform improvements for warehouse cost management, compute efficiency, access control, reliability, observability, and developer experience.
• Identify and lead technical initiatives involving orchestration, CI/CD, data access, and internal tooling.
• Drive complex cross-team projects and take responsibility for outcomes.
• Lead monitoring, testing, incident response, alerting, and observability strategy for the data domain.
• Influence infrastructure and architectural decisions with Engineering, Product, Data Science, and other stakeholders.
• Mentor data engineers and analytics engineers through architectural and modeling reviews.
• Integrate AI into data engineering workflows through validated tooling and automation.

Requirements

• 7+ years of data engineering experience, including ownership of end-to-end pipeline architecture.
• Deep experience designing Apache Airflow orchestration workflows across ingestion, transformation, modeling, and serving layers.
• Experience with containerized data infrastructure in production, including service deployment and operational troubleshooting.
• Ability to evaluate and communicate architectural tradeoffs to technical and non-technical stakeholders.
• Experience improving CI/CD practices for data pipelines, including automated testing, validation, and deployment.
• Experience leading incident response and monitoring strategy, including proactive alerting and observability.
• Experience influencing technical decisions across multiple teams or functions.
• Experience mentoring data engineers and reviewing architectural and modeling decisions.

Nice-to-haves

• Experience with Kubernetes-based data infrastructure.
• Experience leading legacy ETL-to-modern-orchestration migrations end to end.
• Familiarity with platform-scale observability and monitoring tools such as Datadog.
• Experience building internal tooling or automation, including AI-assisted tools.

Compensation

• Zone 1: $171,000 - $207,000 total target compensation, including $154,000 - $182,000 base salary, plus equity.
• Zone 2: $158,000 - $191,000 total target compensation, including $142,000 - $168,000 base salary, plus equity.
• Zone 3: $145,000 - $176,000 total target compensation, including $130,000 - $155,000 base salary, plus equity.
• Compensation targets vary based on work location, skills, experience, education, training, and other job-related factors.