Cloud data platform engineer

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.

• 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.
• You will 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.

• 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.
• Будет плюсом: 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

• Условий в вакансии нет