Senior Data Engineer

Job not on LinkedIn

🔥 2 minutes ago

🇺🇸 United States – Remote

💵 $170k - $200k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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Keebo

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

📦 Logistics

📣 Marketing

💰 Series A on 2022-10

Consulting • Logistics • Marketing

Keebo is a company specializing in fully automated optimization solutions for Snowflake data warehouses. Known as "The Snowflake Savings Machine," Keebo uses its patented technology to automatically adjust settings like warehouse size, clustering, and memory to save customers significantly on their Snowflake costs. The platform is designed to be user-friendly and secure, using only telemetry metadata while offering full visibility and control over optimizations. Setup is simple, requiring only 30 minutes, and users can start realizing savings within 24 hours without impacting performance. Keebo's solution stands apart by delivering real-time cost optimizations and performance protection continuously, unlike other tools that only report data without taking proactive actions.

📋 Description

• 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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