Principal Data Engineer

Principal Data Engineer Santa Monica, CA - Option for Remote 8-month contract with potential to renew Rate Range: $70 - $85/hr, W2 +Benefits Sought Skills & Experience: 1. 8+ years of experience in data engineering or backend data systems. 1. 2+ years of real-time, low-latency architectures. 1. Deep understanding of data storage and messaging tradeoffs (Redis, DynamoDB, Cassandra, or similar). Role Description: As a Principal Data Engineer focused on personalization, social systems and matchmaking within the within the Publishing Platform Data team, you will lead the technical design and implementation of data systems that power personalization, social interactions and matchmaking both in and around-game to ensure a best-in-class experience for our players. You’ll build the foundational data pipelines and real-time systems that enable seamless voice and text chat, player presence, friend graphs, and skill-based matchmaking. This role is ideal for someone passionate about building scalable, low-latency, data-driven systems that connect players and shape their in-game social experiences. This role requires deep technical expertise, tackling complex telemetry challenges, and collaborating across engineering, analytics, data science, research, and product teams to set best practices, drive automation, and deliver reliable, high-quality, data products that delight our players. Responsibilities: ● Design and implement distributed data systems that support real-time social features (voice/text chat, presence, friends, groups, matchmaking) including independently coding and providing optimizations where applicable. ● Build scalable data pipelines to collect, process, and serve player state, behavioral, and telemetry data for matchmaking logic. ● Implement event-driven and streaming architectures to support low-latency interactions and feedback loops between gameplay and data systems. ● Collaborate with Data Scientists and Game Designers to design and implement data-driven matchmaking algorithms (Elo/Glicko, MMR, engagement-based, skill-based). ● Mentor data engineers across all levels, setting best practices and fostering technical growth while also supporting talent acquisition and interviewing efforts. ● Ensure compliance with privacy, security, and responsible AI guidelines when using user behavioral data (e.g., GDPR, CCPA). ● Communicate technical work clearly to both technical and non-technical audiences, ensuring alignment and transparency. ● Build strong relationships to lead adoption of scalable data architecture standards and governance practices. ● Evaluate and adopt new tools, frameworks, and methodologies to advance data engineering capabilities. ● Be a leader within Data Engineering discipline shaping infrastructure, craft standards, tooling, and organizational best practices Required Qualifications: ● Bachelor's or Master’s degree in Computer Science, Information Systems, Engineering, or a related field. ● 8+ years of experience in data engineering or backend data systems, with 2+ focused on real-time, low-latency architectures. ● Proven experience building personalization systems or matchmaking systems or large-scale player-facing social features, including a strong understanding of ranking, MMR, or matchmaking algorithms, and how to integrate them into live game environments. ● Deep understanding of data storage and messaging tradeoffs (Redis, DynamoDB, Cassandra, or similar). ● Expertise in designing efficient and scalable data models with large data sets across multiple teams and in collaboration with stakeholders. ● Ability to bridge the gap between data science models and production engineering. ● Demonstrated ability to work cross-functionally with engineering, analytics, and product teams. ● Proven experience mentoring and guiding other engineers. Desired Qualifications: ● Experience with voice or chat data systems, moderation pipelines, or real-time communication services. ● Experience building and optimizing feature stores and online/offline data pipelines ● Familiarity with vector databases (e.g., Pinecone, FAISS, Weaviate) or semantic search systems. ● Background in gaming, esports, or large-scale interactive media. ● M.S. or Ph.D. in Computer Science, Data Engineering, or a related technical field.