DevOps Engineer – Data Platforms

Who We Are

We’re not in the wing business. We’re in the flavor business. It’s been our mission to Serve the World Flavor since we first opened in 1994, and we’re just getting started. 1997 saw the opening of our first brand‑partner operated Wingstop location, and by 2002 we had served the world one billion wings. It’s flavor that defines us and has made Wingstop one of the fastest growing brands in the restaurant industry.

Above all else – our success is largely due to our people and our core values, or what we call The Wingstop Way of being entrepreneurial, service‑minded, fun, and authentic. We believe having a strong people foundation centered on these collective values creates a crave‑worthy culture and talented team, as well as ensures our brand is poised for accelerated growth. We all win together.

We’re looking for a Dev Ops Engineer – Data Platforms who designs and operates data infrastructure as a scalable, automated platform — not a manually managed system. This role sits at the intersection of Dev Ops, cloud infrastructure, and application engineering, with deep ownership of Postgre

SQL data platforms running on AWS Aurora. You’ll define how data persistence is built, deployed, evolved, and operated across the organization, enabling teams to move fast without compromising reliability or data integrity. You’ll be hands‑on and highly influential — automating change, guiding schema evolution, optimizing performance, and setting platform standards that scale with the business. If you believe data platforms should be boring in production, automated by default, and engineered for change, this role is for you.

• Own and operate Postgre
  
  SQL and Aurora Postgre
  
  SQL platforms across development, staging, and production
• Ensure availability, durability, performance, security, and recoverability of data services

• Build and evolve database‑as‑a‑platform capabilities that enable safe, repeatable change
• Design and support CI/CD‑driven database workflows, including schema migrations, validations, and rollbacks
• Partner with Dev Ops and Platform Engineering teams to align data platforms with cloud and infrastructure standards

• Collaborate with application engineers on schema design, indexing strategies, and data modeling
• Lead and support zero/low‑downtime schema changes using backward‑compatible patterns
• Establish engineering standards that make data models easy to evolve without disrupting production systems

• Proactively monitor and tune database performance through query optimization, indexing, vacuum tuning, and configuration
• Build dashboards, alerts, and capacity plans to keep systems ahead of growth
• Participate in incident response and post‑incident remediation focused on long‑term platform resilience

• Work directly with engineering teams to diagnose and resolve application‑level data and performance issues
• Provide guidance on efficient query patterns, transaction management, and data access strategies
• Contribute SQL, functions, views, and supporting utilities when needed to enable safe production operations

• Design and manage backup, replication, failover, and disaster recovery strategies in AWS
• Ensure best practices around access control, encryption, auditing, and compliance for data platforms

• Data Platforms:
  Postgre
  
  SQL, AWS Aurora PostgreSQL
• Cloud: AWS (RDS, IAM, monitoring, backups)
• Languages:
  
  SQL (expert), working familiarity with application languages (e.g., C#, JavaScript)
• Change Management:
  Flyway, Liquibase, or similar migration tooling
• Dev Ops:
  Git Hub Actions, CI/CD pipelines, infrastructure‑as‑code collaboration
• Monitoring:
  Cloud Watch, performance insights, custom dashboards
• Ways of Working:
  Agile, product‑aligned engineering teams

• 5+ years of experience building and operating Postgre
  
  SQL‑based data platforms in production
• Strong hands‑on experience with AWS Aurora PostgreSQL
• Deep expertise in Postgre
  
  SQL internals, performance tuning, and indexing strategies
• Proven experience executing live schema…