Software Engineer, Data Infrastructure

About the role

Summary

Scopely Explore (formerly known as Niantic) seeks a Software Engineer to design and build the data infrastructure and experimentation platforms that power our mobile games. You will develop systems that help game, product, analytics, and engineering teams run trustworthy experiments, understand player behavior, and make better decisions at scale.

This is a hands-on technical leadership role. You will write production code, make foundational architectural decisions, and operate critical distributed systems while guiding the technical direction of the platform. Beyond individual technical contribution, you will help lead and grow the Data Infrastructure organization by aligning engineers and cross-functional partners, mentoring engineers, and driving multi-team initiatives from strategy through delivery. Depending on team structure and business needs, this role may also include formal people-management responsibilities. We seek creative engineers with excellent technical judgment, strong interpersonal skills, and an eagerness to embrace new technologies and AI-native development methodologies. Do you want to build the foundations that enable faster learning and better player experiences across Scopely Explore?

Responsibilities

- You design, build, and operate scalable data infrastructure and experimentation systems for both general product experimentation and game-specific use cases.

- You lead the technical design of capabilities such as experiment assignment, player segmentation, exposure logging, telemetry processing, metric computation, guardrails, and reproducible analysis.

- You build reliable batch and streaming data pipelines using technologies such as Apache Beam, Apache Spark, Ray, Apache Flink, and Apache Kafka.

- You design data platforms on GCP using technologies such as BigQuery, Apache Iceberg, Google Cloud Storage, Kubernetes, Airflow, and Terraform.

- You remain hands-on throughout the development lifecycle, contributing production code and solving complex problems in distributed computing, streaming, orchestration, and storage.

- You develop effective methodologies and guardrails for AI-assisted and agentic engineering, including context management, automated validation, evaluations, human review, and responsible adoption.

- You use AI-native workflows across your end-to-end responsibilities, including architecture exploration, implementation, testing, code review, documentation, debugging, incident response, and platform operations.

- You maintain ownership of the correctness, security, performance, and maintainability of all work produced with AI assistance.

- You evaluate new technologies pragmatically and apply them where they materially improve engineering velocity, platform reliability, or experimentation quality.

- You lead the technical direction and delivery of the Data Infrastructure, aligning engineers and cross-functional partners around shared priorities, architectural decisions, trade-offs, and multi-quarter execution plans.