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, with a passion for migrating legacy data systems into modern, automated workflows.
- Deep expertise in managing MS SQL Server on AWS infrastructure (EC2, S3, CloudWatch).
- Proficiency 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.
Additional Information
- You will have completed an audit of our data deployment processes and identified the top three bottlenecks in our current release cycle.
- You will have implemented automated CI/CD for database schema changes, leading to a measurable reduction in deployment-related downtime.
- You will own the 'Data as Code' strategy, ensuring our data layer is as agile and resilient as our application layer.
- 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.
- We are committed to providing reasonable accommodation to applicants with disabilities. If you require accommodation for interviewing or otherwise participating in the employee selection process, please provide more detail on how we can further support you by reaching out to the Employee Experience department.
- We are committed to full compliance with all applicable labor laws, including Equal Employment (EEOC) laws, across all our company entities.
- We have human oversight in all hiring decisions. If you have concerns regarding the use of AI in your assessment, please contact Panopto Talent Attraction to request a manual review of your application. Please be aware that while we offer this option, the manual review process may take longer than the standard AI-assisted process. Any data collected during this process, including video recordings if applicable, will be retained only for the duration necessary to fulfill the hiring purpose and will be deleted shortly thereafter once the role is filled. We may utilize vendor tools to assist with the AI process. Vendor functions are ‘skill assessments' or 'resume analysis'.
