Job description

Our client is an established consumer marketplace using machine learning and generative AI to help millions of renters find homes they love. Founded in 2009, the platform includes more than six million rental units and has raised approximately $169M. The company is entering an AI-first chapter while modernizing the revenue, Salesforce, and data foundations that support its marketplace. We are hiring a Senior Data Engineer II to own end-to-end data-pipeline architecture across a lean, high-impact platform team. This is an IC4 role for an engineer who remains hands-on with code and production operations while independently making architectural decisions, evaluating platform investments, and guiding other engineers. You will shape how analytics engineering, data science, and product engineering teams build on the platform. What you'll do • Own architecture across ingestion, transformation, modeling, and serving layers • Design platform improvements for warehouse cost, compute efficiency, access control, reliability, and observability • Lead large cross-functional projects and multiple concurrent technical initiatives from design through delivery • Build monitoring, testing, and alerting that closes production visibility gaps before failures occur • Improve orchestration, CI/CD, data access, and developer experience across the platform • Mentor data and analytics engineers and serve as a technical peer on architectural and modeling decisions • Build practical AI-powered tooling and automation that creates leverage for the broader team • 6 to 9 years of experience as a data engineer or data platform engineer • Strong, hands-on SQL and Python skills that hold up in a live technical environment • Production experience with containerized data infrastructure, including deployment and operational troubleshooting • Production experience with a pipeline orchestrator such as Airflow and a cloud data warehouse such as BigQuery • A track record of owning pipeline architecture end to end and explaining tradeoffs to technical and non-technical stakeholders • Experience making sound decisions across freshness, cost, scalability, reliability, and simplicity • US work authorization without current or future visa sponsorship Bonus points • Experience with Kubernetes, Datadog, CI/CD, or warehouse-cost optimization • Experience at both an established mid-sized technology company and a startup or smaller product organization • Familiarity with Salesforce data integrations or major data-platform migrations • Experience coaching other engineers on safe, validated uses of AI in data workflows • Base salary of $145K-$207K • Competitive equity • Strong emphasis on sustainable pace and work-life balance • High ownership on a small data-platform team with meaningful greenfield work • Fully remote within the United States • Opportunity to attend company on-sites up to four times per year • Full-time senior individual-contributor position

Requirements

Must-haves

Own architecture across ingestion, transformation, modeling, and serving layers
Design platform improvements for warehouse cost, compute efficiency, access control, reliability, and observability
Lead large cross-functional projects and multiple concurrent technical initiatives from design through delivery
Build monitoring, testing, and alerting that closes production visibility gaps before failures occur
Improve orchestration, CI/CD, data access, and developer experience across the platform
Mentor data and analytics engineers and serve as a technical peer on architectural and modeling decisions
Build practical AI-powered tooling and automation that creates leverage for the broader team
6 to 9 years of experience as a data engineer or data platform engineer
Strong, hands-on SQL and Python skills that hold up in a live technical environment
Production experience with containerized data infrastructure, including deployment and operational troubleshooting
Production experience with a pipeline orchestrator such as Airflow and a cloud data warehouse such as BigQuery
A track record of owning pipeline architecture end to end and explaining tradeoffs to technical and non-technical stakeholders
Experience making sound decisions across freshness, cost, scalability, reliability, and simplicity
US work authorization without current or future visa sponsorship

Nice-to-haves

Experience with Kubernetes, Datadog, CI/CD, or warehouse-cost optimization
Experience at both an established mid-sized technology company and a startup or smaller product organization
Familiarity with Salesforce data integrations or major data-platform migrations
Experience coaching other engineers on safe, validated uses of AI in data workflows
Competitive equity
Strong emphasis on sustainable pace and work-life balance
High ownership on a small data-platform team with meaningful greenfield work
Fully remote within the United States
Opportunity to attend company on-sites up to four times per year
Full-time senior individual-contributor position

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaici/cdsqlpythonkubernetes

Platform: workable
Effort: medium