The Director of Data Engineering will lead and scale the Data Engineering and Analytics Engineering functions, owning the post-application data platform and its architecture, governance, and operating model. This foundational leadership role ensures best in class engineering standards, helps drive the organization toward a durable, auditable, data-product operating model, and modernizes and expands a Snowflake-centered data stack to include building and operating scalable distributed data processing and real-time streaming systems that support event-driven data products for operational use cases.

The role partners closely with Product, Software Engineering, Data Product Managers, Marketing, Compliance, Finance and Data Science to ensure our data ecosystem is production-grade, scalable, and compliant in a regulated gaming environment.

What You'll Do:

Team Leadership & Organizational Growth

• Lead and grow Data Engineering and Analytics Engineering teams; recruit, mentor, and elevate technical capabilities around distributed data processing, stream processing, and event-driven architectures
• Define ownership models for platform components and data products; set performance and hiring plans.
• Advance engineering standards for deployment: development, testing, documentation, release management, and SLAs.
• Partner with Data Product Managers to define data assets as versioned, documented data products with clear ownership and SLAs.

Platform, Architecture & Engineering Excellence

• Own the administration, reliability, governance, and strategic expansion of the Snowflake-based post-application data platform to operate scalable distributed data processing pipelines capable of handling high-volume event data across both batch and streaming workloads.
• Manage platform governance, access control, security, cost, and capacity planning.
• Standardize DBT deployment methods, promotion workflows, and environment management.
• Implement Infrastructure-as-Code (Terraform or similar) for reproducible, auditable infrastructure.
• Deliver monitoring, observability, lineage, and data quality frameworks; enforce traceability and auditability for regulated reporting.
• Own and evolve ingestion and warehouse architecture and transformation frameworks .
• Improve performance, cost efficiency, reliability, and scalability of data transformation and storage layers.
• Define and enforce engineering standards across the data lifecycle and establish SLAs and reliability metrics for critical assets - ensuring all pipelines, transformations, and reporting are auditable and documented for internal and external review

Event-Driven Architecture & Player 360

• Partner with Software Engineering on event messaging, streaming architecture, and ingestion patterns (built on technologies such as Kafka, Kinesis, Spark Structured Streaming, Flink, or equivalent platforms).
• Lead technical design and development of a unified Player 360 data foundation that integrates transactional, behavioral, and event-level data.
• Align application schema design with downstream analytical, product, and regulatory requirements.
• Balance real-time and batch processing strategies according to business needs and cost/complexity tradeoffs.

What You'll Bring:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related STEM field preferred. Equivalent practical experience will be considered.
• 8+ years of experience in data engineering, with 3+ years of experience in leadership roles. 
• Experience transitioning an organization from private/startup to public company.
• Experience in regulated industries (gaming, fintech, payments, healthcare).
• Prior experience building Player 360 / Customer 360 platforms.
• Deep hands-on experience with Terraform / IaC and production-grade streaming systems (Kafka, Kinesis, etc.).
• Familiarity with GenAI governance frameworks and scalable AI integration patterns such as Harness Engineering.
• Able to travel occasionally both domestically and internationally. #LI-REMOTE #LI-PROMOTE