DataOps Engineer
AI Summary
DataOps Engineer responsible for architecting automated, code-driven data infrastructure and pipelines on AWS, bridging operational, analytics, and AI data layers.
About this role
Company Overview:
At Panopto, we are the most customer-centric learning technology company in the world. As the leader in visual and audio-based learning, we empower organizations to share knowledge effortlessly in a capture and post-capture world. We don’t just build software; we obsess over our users’ goals to deliver solutions that truly matter. Our mission is simple: to attract the brightest talent, people like you, to Elevate the Craft and do the most impactful work of your career.
As we scale our global reach, we are seeking a DataOps Engineer to architect the 'Golden Path' for our data infrastructure. You will transform how we manage the data powering Panopto for 10+ million users by replacing manual database management with automated, code-driven pipelines that enable seamless growth and rapid innovation.
Position Summary:
In this role, you will have the opportunity to do the most impactful work of your career, elevating your craft while contributing to a team that values lifelong learning.
You will engineer the lifecycle of our most critical asset: data. Your mission is to bridge the gap between Operational, Analytics, and AI data layers by treating infrastructure as code. You’ll eliminate bottlenecks in our AWS-hosted SQL Server environment, building automated, reliable pathways that ensure data is not just delivered, but is architecturally optimized for both real-time operations and long-term machine learning scalability. You'll also have opportunities to contribute to other initiatives that directly advance our core values and support you in elevating your craft.
How You’ll Contribute:
In this role, you will have the opportunity to…
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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.
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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).
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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.
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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.
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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.
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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.
How We Thrive:
You’ll join a team of talented engineers—from DevOps to Design—where we challenge ideas, not people. We believe our success depends on our Collective Wisdom, supporting each other through complex projects and celebrating continuous improvement.
The Foundation for Success:
The DataOps Mindset: You have 5+ years of experience in DevOps or Database Administration, with a passion for migrating legacy data systems into modern, automated workflows.
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AWS & SQL Mastery: You bring deep expertise in managing MS SQL Server on AWS infrastructure (EC2, S3, CloudWatch).
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Automation Fluency: You are proficient in Python, Bash, or PowerShell and have a working knowledge of C# to build robust automation scripts that bridge the gap between application and data.
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Outcome-Oriented: You Act with Ownership, focusing on results that improve the daily quality of life for the entire engineering team.
What Success Looks Like:
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Within 6 Months (Integration & Audit): You will have completed an audit of our data deployment processes and identified the top three bottlenecks in our current release cycle.
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Within 1 Year (Measurable Impact): You will have implemented automated CI/CD for database schema changes, leading to a measurable reduction in deployment-related downtime.
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Your Legacy (Full Ownership): You will own the "Data as Code" strategy, ensuring our data layer is as agile and resilient as our application layer.
As a DataOps Engineer, you aren't just managing a database; you are building the automated engine that ensures knowledge is accessible, secure, and reliable at a global scale. Join us to move the needle on data agility and Elevate the Craft of modern engineering.