Senior Data Engineer
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Job Description
Senior Data Engineer scaling data pipelines and MLOps infrastructure for Keebo’s cloud warehouse optimization platform. Building reliable models, features, and AI-enabled engineering workflows.
Responsibilities:
- Design and build reliable data pipelines processing large volumes of customer warehouse data
- Build and run machine learning operations infrastructure for feature pipelines, training jobs, deployment, and monitoring
- Own data quality and data modeling for accurate, trustworthy model and customer-facing feature data
- Use AI coding tools by writing clear specifications and context, running agents on parallel workstreams, and critically reviewing output
- Build shared AI workflows, guardrails, and review standards
- Evaluate new tools and models and share worthwhile ones with the team
- Write architecture documentation explaining systems, tradeoffs, and rationale
- Understand customer needs and determine what is worth building
- Mentor engineers, including on effective use of AI coding tools
Requirements:
- 5+ years of data engineering or software engineering experience, including time at an early-stage startup (Seed through Series B)
- Deep experience building and scaling production data pipelines, batch and streaming, particularly with Dagster, Airflow, or Temporal
- Hands-on machine learning operations experience: deploying, monitoring, and retraining models in production
- Strong data modeling and architecture skills, and a track record of keeping data quality high as volume grows
- Deep experience with AI coding agents, and examples of how to scale their use across a team
- Judgment to catch AI output that is wrong, incomplete, or risky, especially with customer data
- Proven expertise in SQL and Python
- Experience with cloud platforms, workflow orchestration, containers, and automated deploy pipelines
- Clear, collaborative communication, especially in writing
- Persistence and a constructive attitude when things break or plans change
- Must live in the United States and be authorized to work there
- Visa support will not be provided
Benefits:
- Equity
- Medical, dental, and vision benefits
- 401(k) retirement program
- Home office stipend
- Paid time off and paid parental leave
- The latest AI tools, and freedom to try new ones
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