About
At Scopely, we care deeply about what we do and want to inspire play every day - whether in our work environments alongside our talented colleagues or through our deep connections with our communities of players. We are a global team of game lovers who are developing, publishing, and innovating the mobile games industry, connecting millions of people worldwide daily. Playgami builds technology for game teams across Scopely.
Responsibilities
As a Senior Data Platform Engineer, you will build and improve the shared infrastructure, tooling, and services that power data and analytics teams across Scopely. You will investigate platform needs, evaluate technical tradeoffs, and turn agreed priorities into tested code and reusable infrastructure. Working closely with data and analytics teams, Security, and Governance, you will take platform improvements from technical design through deployment and operation. Your main responsibility will be to improve the security, reliability, scalability, and efficiency of our Data Platform while making it easier for teams to build and operate their data workloads.
•Lead the technical design and delivery of platform improvements, making informed tradeoffs between reliability, security, scalability, and cost as part of a shared team roadmap
•Build and operate shared GCP and BigQuery infrastructure using Terraform, automated checks, and CI/CD
•Build scalable, self-service platform capabilities that enable data teams to develop, deploy, and operate workloads with less manual support
•Improve user and service account access, ensuring least-privilege principles and dependable approval, review, and revocation processes
•Translate Security and Governance requirements into practical controls for sensitive data and data sharing
•Improve Airflow and Cloud Composer reliability through troubleshooting, staged upgrades, and tested recovery processes
•Improve cloud data platform performance and cost efficiency using workload and capacity insights
•Build actionable monitoring and alerts, investigate incidents, and implement improvements to prevent recurring failures
•Partner with teams to understand their needs, investigate platform challenges, evaluate potential solutions, and help shape the technical roadmap
•Make platform workflows easier to adopt and operate through documentation, runbooks, and mentoring
•Provide infrastructure, access controls, and shared tooling that help teams use data safely and reliably at scale
Requirements
•Experience designing, deploying, and operating production cloud or data platforms, including safe releases and recovery
•Hands-on experience with GCP, BigQuery, IAM, service accounts, and Cloud Storage, or strong equivalent cloud experience
•Experience authoring Terraform and CI/CD workflows, testing infrastructure changes, and resolving drift
•Experience with Python for reusable automation and SQL for investigating data and workload behavior
•Experience implementing and validating least-privilege access, sensitive data controls, and audit logging
•Experience operating Airflow, Cloud Composer, Dagster, or a similar workflow orchestrator
•Demonstrated experience reducing manual work or improving platform reliability, workload performance, or cloud costs
•Strong English communication skills and experience collaborating with engineering, security, and data teams
•We value production ownership, sound engineering judgement, and the ability to learn
•Relevant experience can come from data platform, cloud infrastructure, software engineering, DevOps, or site reliability roles
Nice to have
•Experience with BigQuery reservations, capacity management, query optimization, and cost attribution
•Experience with Cloud Composer migrations or upgrades, multi-environment orchestration, and recovery testing
•Experience with Workload Identity Federation, short-lived credentials, access approval integrations, or tools such as Britive and Lumos
•Experience with data classification, column-level controls, masking, controlled sharing, or automated discovery of sensitive data
•Experience automating and operating Looker, dbt, Fivetran, or Cube as shared platform services
•Experience supporting automated data workloads, including access controls, monitoring, and cost limits
•Experience using AI-assisted tools for platform automation, troubleshooting, or documentation, with appropriate testing and review
Conditions
Not stated in the posting.
