DataOps Engineer

Panopto is a customer-centric learning technology company that empowers organizations to share knowledge effortlessly. They are seeking a DataOps Engineer to architect the 'Golden Path' for their data infrastructure, transforming data management with automated, code-driven pipelines while ensuring data quality and availability across multiple layers.

Responsibilities:

• Engineer the Data Lifecycle: You will design and implement the "Golden Path" for data, ensuring seamless transitions between operational SQL environments, analytics warehouses, and AI-ready data sets
• Implement Data as Code: You’ll move beyond manual administration by treating our AWS-hosted MS SQL infrastructure as a version-controlled, automated ecosystem using CI/CD and Infrastructure as Code (IaC)
• Architect Multi-Layer Reliability: You will build the frameworks that guarantee data quality and availability across all tiers—from high-concurrency operational databases to the complex feature stores used by our AI and Machine Learning models
• Optimize for Scalability & Performance: You’ll identify and resolve architectural bottlenecks in our massive SQL Server environment, ensuring the system can handle the high-throughput demands of modern SaaS analytics
• Standardize Data Observability: You will develop advanced monitoring and alerting strategies that provide deep visibility into data health, ensuring that operational and analytical layers remain performant and trustworthy
• Bridge the Engineering Gap: You’ll collaborate with Software Engineers and Data Scientists to ensure the data architecture supports both rapid product iteration and long-term research initiatives

Requirements:

• 5+ years of experience in DevOps or Database Administration
• Deep expertise in managing MS SQL Server on AWS infrastructure (EC2, S3, CloudWatch)
• Proficient in Python, Bash, or PowerShell
• Working knowledge of C# to build robust automation scripts
• Ability to treat AWS-hosted MS SQL infrastructure as a version-controlled, automated ecosystem using CI/CD and Infrastructure as Code (IaC)
• Experience in designing and implementing data lifecycles
• Ability to identify and resolve architectural bottlenecks in SQL Server environments
• Experience in developing advanced monitoring and alerting strategies for data health
• Ability to collaborate with Software Engineers and Data Scientists
• Focus on results that improve the daily quality of life for the engineering team