Lead Data Technical

About the Role Quality Foundations (QF) develops data-driven products and services that support Ubisoft games. The Lead Data Technical defines and evolves the data foundations, acting as the primary technical authority for data architectures and analytics platforms within QF. They design, operate, and optimize robust, scalable data solutions for development, production, analytics, and AI teams. What You'll Do

• Collaborate with architects to design new data products and scalable solutions.
• Implement and drive adoption of the target data architecture across teams.
• Serve as the subject matter expert for data, architectures, and processing pipelines.
• Provide technical leadership across QF regarding data storage, modeling, governance, and processing.
• Define, maintain, and promote data standards and best practices; review ADRs and ensure decisions are adopted.
• Lead high-complexity initiatives; advise on technology directions to improve data platforms.
• Analyze and optimize performance, cost efficiency, reliability, and scalability of data systems.
• Act as SME for relational and non-relational database optimization.
• Collaborate with development, analytics, AI, and operations teams to ensure seamless data solution integration.
• Ensure technical quality of data pipelines and promote monitoring, alerting, and operations best practices.
• Foster knowledge sharing and autonomy within data development teams.
• Participate in evaluating new technologies, platforms, and data approaches.
• Perform other related duties as required. What We're Looking For
• Education: Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or equivalent.
• Experience: ≥8 years in software development or data engineering; experience designing and implementing large-scale data platforms; technical leadership and distributed architectures.
• Skills and Knowledge: Strong SQL/NoSQL data modeling; proficiency in Python, PySpark, SQL, and Scala; knowledge of Medallion architectures (Bronze/Silver/Gold) and Lakehouse platforms (Databricks, Delta Lake).
• Experience with pipeline-as-code, environment-agnostic design, and documentation of architectural decisions.
• Technical Assets: Cloud services (AWS/Azure), Docker, Kubernetes; Airflow or Databricks Workflows; Spark Structured Streaming; Databricks, Spark, Delta Lake, Elasticsearch/OpenSearch, SQL Server, PostgreSQL; monitoring and alerting; ML/AI concepts; real-time systems.
• Professional Competencies: Analytical problem-solving; mentoring; IaC and declarative pipelines; strong communication; leadership; multi-disciplinary collaboration; initiative and prioritization. Nice to Have
• Experience in high-volume, real-time telemetry/observability environments is a significant asset.