Staff Data Engineer

About the Role #2991

We are seeking a Staff Data Engineer for a global leader in competitive gaming and live-service entertainment. In this role, you will serve as a premier technical leader within our global data platform domain, driving the design, architecture, and scaling of core data infrastructure that transforms raw data assets into production-grade pipelines. You won't just be managing data; you will be building and optimizing the highly complex data systems that keep massive, live-service global games running smoothly, ensuring optimal performance for millions of players.

This role requires a high-autonomy engineer who thrives in ambiguous environments and naturally takes the initiative on large-scale infrastructure challenges. Operating at the intersection of game tech and live operations, you will take end-to-end ownership of data platforms from conception to delivery. Collaborating directly across engineering, data science, and product management teams, you will operate with immense self-direction to deliver technical realities that directly impact our global player base.

Most Important

• A proven, production-tested track record handling large-scale, highly complex enterprise data environments with a history of owning and driving mission-critical projects from scratch
• .Deep fluency in Python and Apache Spark for heavy distributed data processing, performance tuning, and compute optimization
• .Direct, hands-on production experience configuring, deploying, and managing Databricks, Snowflake, dbt (Data Build Tool), and Apache Airflow ecosystems
• .Fluent English (written and verbal) is strictly required to successfully articulate engineering trade-offs, navigate ambiguous technical spaces, and coordinate crisis management during on-call incidents without needing micromanagement
• .Strictly restricted to Mexico or Brazil (Remote), with the ability to maintain a minimum 6-hour daily overlap with Pacific Standard Time (PST/PDT)
• .Willingness and ability to participate in a disciplined production on-call rotation every 5–7 weeks to triage line failures, diagnose data drift, and ensure platform uptime

.Nice to Have

• AWS Cloud Literacy — Practical comfort navigating AWS infrastructure components (e.g., S3, EC2, IAM, EMR) to manage data lakes, storage tiers, compute clusters, and system security permissions
• .Pipeline Architecture & Scaling— Experience designing and implementing both robust batch and streaming high-throughput data pipelines using Spark and Python
• .Data Transformation & Modeling —Experience building and governing scalable, highly performant data warehouse models using dbt inside Snowflake environments
• .Cross-Functional Collaboration — Prior experience partnering directly with Data Scientists, Analytics Engineers, and Product Managers to map shifting data requirements into scalable engineering realities

.Personal Traits

• The "Data Detective" —You possess elite debugging instincts. When a complex pipeline fails or data drift occurs, you dig deep into fragmented systems to uncover root causes that others completely miss
• .The Project Owner — You don’t just complete tickets or wait for directions; you proactively identify system bottlenecks, propose architectural solutions, and take full accountability for end-to-end delivery
• .Comfort with Ambiguity — You thrive when the path forward isn't clearly defined. You enjoy taking a vague operational or data problem, structuring it, and rallying cross-functional stakeholders toward a solution
• .Player-Focused Mindset — You treat data infrastructure as a means to deliver value, constantly finding creative solutions to efficiency and infrastructure puzzles because you care about the ultimate player experience
• .Influential Leader — You act as a technical pillar who naturally elevates the organization's technical bar, articulates clear engineering trade-offs, and guides complex initiatives forward with a steady hand

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