Lead Technique Données (TGQF)

Ubisoft•Montreal, QC

7d•Onsite

About The Position

Quality Foundations (QF) develops and operates cross-functional products, platforms, and services to improve the quality, observability, performance, and operation of Ubisoft games through data, analytics, and artificial intelligence. In this context, the Lead Technical Data plays a key role in defining and evolving the data foundations supporting QF's various products. The holder of this position is the technical reference for all data-related issues, data architectures, and analytical platforms within Quality Foundations. They act as a principal expert to ensure the design, evolution, and operation of robust, high-performance, and scalable data solutions that meet the needs of development, production, analytics, and artificial intelligence teams. In close collaboration with architects, development teams, and product managers, they contribute to defining, implementing, and evolving the organization's target data architecture. They ensure the application of best technical practices, the consistency of solutions across the entire Quality Foundations product portfolio, and the alignment of initiatives with the company's strategic directions.

Requirements

Bachelor's degree in computer science, computer engineering, software engineering, or any equivalent training.
Minimum of 8 years of experience in software development or data engineering.
Significant experience in designing and implementing large-scale data platforms.
Experience in technical leadership, team support, or mentoring.
Experience with distributed architectures and big data processing systems.
Excellent command of big data solution development and SQL and NoSQL data modeling.
Excellent command of one or more of the following languages: Python, PySpark, SQL, and Scala.
Solid understanding of modern data architectures, processing pipelines, and analytical platforms, including medallion architectures (Bronze/Silver/Gold) and lakehouse platforms (Databricks, Delta Lake).
Experience in designing configurable and environment-agnostic solutions (dev/staging/prod), with a mastery of pipeline-as-code and configuration management practices.
Ability to design scalable, performant, and maintainable solutions.
Experience in documenting architectural and technical decisions.
Excellent analytical and synthesis skills.
Strong ability to solve complex problems.
Aptitude for mentoring and developing the technical autonomy of team members.
Sensitivity to configuration-oriented approaches: preference for configurable systems, declarative pipelines, and reproducible deployments (infrastructure as code).
Excellent communication and technical popularization skills.
Influence leadership and ability to mobilize teams around best practices.
Ability to work effectively in a multidisciplinary environment.
Initiative and autonomy.
Results-oriented and focused on continuous improvement.
Ability to manage multiple issues simultaneously and set the right priorities.

Nice To Haves

Knowledge of cloud services (AWS, Azure, or others), as well as Docker and Kubernetes technologies.
Knowledge of data orchestration frameworks such as Apache Airflow or Databricks Workflows.
Knowledge of real-time data streaming (Spark Structured Streaming or equivalent).
Knowledge of Databricks, Apache Spark (batch and streaming), Delta Lake, Elasticsearch/OpenSearch, SQL Server, and PostgreSQL.
Knowledge of large data system administration as well as relational and non-relational databases.
Knowledge of monitoring, logging, and alerting systems for data pipelines.
Understanding of concepts related to machine learning and artificial intelligence.
Experience in a critical system context with high volumes of real-time data (telemetry, observability, monitoring) is a significant asset.

Responsibilities

Collaborate with architects and contribute to the design of new data products and services by proposing robust, scalable solutions aligned with organizational needs.
Participate in the implementation of the target data architecture and ensure its adoption within teams.
Act as the go-to person for all data-related issues, data architectures, and processing pipelines.
Provide technical expertise to all Quality Foundations products regarding data storage, modeling, governance, and processing.
Define, maintain, and promote data standards and best practices within QF, and oversee their application across teams.
Propose, review, and validate technical and architectural decisions through Architecture Decision Records (ADR), and ensure the adoption of accepted decisions within teams.
Actively participate in the development and execution of initiatives presenting the highest levels of complexity or risk.
Advise architects, project managers, and managers on technological directions and improvements to data platforms.
Analyze and optimize the performance, costs, reliability, and scalability of data systems.
Act as an expert in optimizing relational and non-relational databases.
Collaborate with development, analytics, artificial intelligence, and operations teams to ensure the seamless integration of data solutions.
Ensure the technical quality of data pipelines and promote best practices for monitoring, alerting, and operations.
Foster knowledge transfer, mentoring, and the development of technical autonomy for data developers.
Participate in technical evaluations of new technologies, platforms, or data-related approaches.
Perform all other related tasks.