Please note that Digital Turbine is a hybrid work environment-only candidates local to the posting location will be considered.The RoleThe Tech Platform organization maintains and evolves the foundational platform and shared services that every other DT workstream depends on. As we assemble siloed products into a single marketplace, getting the platform right - reliable, observable, standardized, and cost-efficient - is the critical variable for execution at marketplace scale.
As a Senior Infrastructure Engineer, you'll design and operate the large-scale distributed systems, data infrastructure, and deployment platforms that serve tens of billions of daily events. You'll help drive our OneDT standardization - including the migration to GitOps/ArgoCD and unified CI/CD - and build the platform capabilities (including ML and data infrastructure) that the rest of engineering builds on.
About the Senior Infrastructure Engineer Role- Design, build, and operate large-scale distributed systems and data platforms for reliability, scalability, and cost-efficiency
- Drive the OneDT platform standardization: GitOps/ArgoCD adoption, unified CI/CD pipelines, and a clear developer-ownership model across business lines
- Build and operate Kubernetes-based infrastructure, including Spark-on-K8s and data/ML platform tooling (e.g., Databricks ecosystems)
- Implement MLOps and data-pipeline capabilities - training, deployment, and serving infrastructure - in partnership with ML and Data teams
- Champion observability, automation, and cost-optimization initiatives that improve reliability while reducing spend
- Participate in on-call rotations, lead incident response and blameless postmortems, and prevent recurrence through automation and platform improvements
About You as the Senior Infrastructure Engineer- 8+ years in infrastructure, platform, or back-end engineering, with a track record of building robust distributed systems
- Deep experience with a major cloud provider (AWS or GCP; Azure a plus) and proficiency in Go, Java, Python, or Scala
- Strong hands-on experience building and operating Kubernetes infrastructure stacks.
- Familiarity with data and/or ML infrastructure: Spark, Kafka, data lakes, Databricks, or comparable technologies
- Experience with infrastructure-as-code, CI/CD, GitOps, and modern observability tooling
- Operational maturity: you've owned production systems, run on-call, and improved reliability systematically
Nice to have- Experience leading large migrations or platform-standardization programs across multiple teams
- Background in high-throughput, low-latency systems such as real-time bidding or event streaming
- Experience with cost governance (FinOps) at scale
