Data Engineer (L5) - Games

Position Overview

At Netflix, our mission is to entertain the world. We are pushing the boundaries of storytelling and technology as we enter our next big frontier – games – to deliver new experiences for our growing global membership. In the Data Science and Engineering team, as a Senior Data Engineer focused on Core Metrics and Metadata, you will leverage high-quality data to support end-to-end analytics for our Games partners and help redefine what a Netflix subscription means.

Key Responsibilities

• As a Senior Data Engineer, your focus will be on architecting the foundation for all business measurements across our games portfolio on all platforms.
• Own Core Metric Systems: Design, develop, and maintain the single source of truth for core business and operational metrics (e.g., DAU/MAU, retention, engagement rates) to ensure consistency, explainability, and reliability.
• Data Modeling Architecture: Create advanced analytical data models (facts, dimensions, aggregations) optimized for performance, partitioning, and backfill considerations.
• Implement High-Reliability Pipelines: Build and optimize robust, high-volume data pipelines using distributed processing frameworks such as Spark, Flink, Python, and Scala, tackling challenges like event-time partitioning and late data handling.
• Data Governance and Quality Leadership: Define and enforce data quality standards and implement data lineage tracking to support accurate interpretation of core metrics.
• Strategic Collaboration: Partner with Games Product, Data Science, and Engineering stakeholders to translate forecasting, research, and analytical needs into scalable data solutions.
• Technical Leadership: Champion best practices in data engineering and software development, proactively resolve technical debt, and mentor junior team members.

Required Qualifications

• Experience Required: 7+ years of hands-on experience in software development with a deep focus on building high-performance data systems for telemetry data analytics.
• Expert-level Data Modeling: Proven mastery in designing event schemas and analytical (dimensional) models, including aggregation strategies and partitioning considerations.
• Distributed Processing Mastery: Demonstrated experience with production-grade data pipelines using frameworks such as Spark, Flink, and Hive/Hadoop along with a strong understanding of distributed systems.
• Advanced Data Processing: Hands-on experience with batch and streaming data processing patterns, including CDC, incremental loads, and event-driven architectures.
• Programming & SQL: Expert proficiency in Python and/or Scala/Java along with mastery of SQL, maintaining a strong software engineering mindset.
• Strong Partnership Skills: Exceptional communication abilities with proven experience in collaborating with non-technical stakeholders and driving cross-functional engineering projects.

Benefits & Perks

• Benefits: Comprehensive health plans, mental health support, a 401(k) retirement plan with employer match, and a stock option program.
• Additional benefits include disability programs, health savings and flexible spending accounts, family-forming benefits, and life & serious injury benefits.
• Paid leave programs: Full-time hourly employees accrue 35 days annually for vacation, holidays, and sick leave, while salaried employees enjoy flexible time off.