Senior Infrastructure Engineer, Upstart

• We would love to hear from you if you are passionate about infrastructure and observability!
• A bachelor's degree in Computer Science or a related field
• 5+ years of experience in infrastructure engineering, DevOps or related fields, with a strong focus on data infrastructure (bonus)
• Hands-on experience in AWS cloud services (EC2, SQS, S3, Lambda, EKS)
• Strong experience working with Python or similar scripting languages
• Strong DevOps/SRE knowledge and expertise in multiple areas, including scripting, IaC, automation, configuration management, and containerization/container orchestration (Kubernetes)
• Ability to approach problems with first principles thinking, embrace ambiguity, and enjoy collaborative work on complex solutions
• Hands-on experience with both open-source and enterprise application performance monitoring solutions

Desirable

• The Data Platform Engineering team (Part of Upstart's Decisioning & Data) provides developer tools, frameworks, and scalable data infrastructure as shared services across Upstart
• The team's primary objective is to provide Data Analysts, ML scientists, and Software Engineers access to high-quality data and developer tools to create business metrics and training data for respective product verticals
• You will join the subdivision that focuses on data infrastructure & observability
• As the Senior Infrastructure Engineer joining this team, you will get the opportunity to contribute to 3 areas:
• Managing the Lakehouse (Databricks) infrastructure, including access control, security, and observability
• Continuously enhance data infrastructure observability, with a focus on cost and usage efficiency within the data engineering space
• Improve the build-test-deploy-monitor pattern for data apps and stack like Change Data Capture, Spark, Kafka, etc
• Help build Upstart's cloud infrastructure that aligns with the overall business objectives by participating in planning and prioritization
• Improve developer efficiency and infrastructure reliability by working with cross-functional stakeholders like Data Engineering, Machine Learning, Analytics, Compliance, and Security
• Improve Lakehouse security, usage efficiency, and observability by collaborating closely with the Data Engineering and Security teams
• Evangelize good coding and engineering best practices while uplifting fellow engineers and mentoring junior team members
• Help break down complex projects and requirements into quarterly commitments and sprints
• Provide top tier support for our data apps and keep them highly available