2 months ago
Tokyo, JapanStaff+
Responsibilities
- Design, build, and operate scalable data infrastructure and experimentation systems for product and game-specific use cases.
- Lead technical design for experiment assignment, player segmentation, exposure logging, telemetry processing, metric computation, guardrails, and reproducible analysis.
- Build reliable batch and streaming pipelines using Apache Beam, Apache Spark, Ray, Apache Flink, and Apache Kafka.
- Design GCP-based data platforms using BigQuery, Apache Iceberg, Google Cloud Storage, Kubernetes, Airflow, and Terraform.
- Contribute production code and solve complex distributed computing, streaming, orchestration, and storage problems.
- Develop guardrails, validation, evaluations, human-review processes, and responsible practices for AI-assisted and agentic engineering.
- Use AI-native workflows for architecture, implementation, testing, review, documentation, debugging, incident response, and operations while owning the resulting work.
- Lead technical direction, shared priorities, architectural decisions, trade-offs, and multi-quarter delivery plans for the Data Infrastructure organization.
- Coach and develop engineers through mentorship, feedback, and technical guidance, with possible formal people-management responsibilities.
Requirements
- Extensive experience designing, building, and operating production data platforms or large-scale distributed systems.
- Strong programming ability in one or more of Java, Python, Go, or Rust; Java or Python experience is especially relevant.
- Deep experience with cloud data infrastructure, preferably GCP and BigQuery.
- Production experience with distributed-computing frameworks such as Apache Beam, Apache Spark, or Ray.
- Experience building real-time data systems with Apache Flink, Apache Kafka, or comparable streaming frameworks.
- Experience with orchestration, containers, and infrastructure automation technologies such as Kubernetes, Airflow, and Terraform.
- Understanding of modern storage and lakehouse architectures, including Apache Iceberg and object storage such as Google Cloud Storage.
- Experience building experimentation, analytics, telemetry, or data products used by multiple engineering and product teams.
- Understanding of trustworthy experimentation, including assignment, exposure tracking, metric definition, data quality, reproducibility, and statistical interpretation.
- Experience setting technical direction and driving complex cross-team initiatives while remaining involved in implementation.
- Demonstrated delivery leadership for complex projects spanning multiple engineers and cross-functional partners from strategy through operational ownership.
- Experience managing and developing engineering teams, including hiring, performance feedback, career growth, and team-culture development.
- Ability to use, evaluate, validate, and take responsibility for AI-native workflows across the engineering lifecycle.
- Clear communication and effective collaboration with distributed, cross-functional teams.
- Proficiency in English; Japanese proficiency is a bonus.
- Ability to design, implement, test, and reason about production-quality software; coding is tested during recruitment.
Benefits
- Position based in Tokyo with flexibility and regular office attendance expected three days per week.
- AI tools are permitted and may be part of the development workflow.
Tech Stack
Apache AirflowApache BeamApache FlinkApache KafkaApache SparkGoGoogle BigQueryGoogle CloudGoogle Cloud PlatformJavaKubernetesPythonRustTerraform
Categories
BackendData Engineering
About Scopely
Scopely develops, publishes, and live-operates free-to-play games across mobile, PC, and console, including MONOPOLY GO!, Stumble Guys, Star Trek Fleet Command, MARVEL Strike Force, WWE Champions, and Yahtzee With Buddies. Founded in 2011 and headquartered in Culver City, California, it uses its Playgami technology platform and collaborates with studios worldwide. In 2023, Scopely was acquired by Savvy Games Group and continues to operate as an independent subsidiary.