{"id":31004,"url":"https://alion.io/job/ubisoft-technical-lead-data-tgqf","title":"Technical Lead Data (TGQF)","company":{"id":3624,"name":"Ubisoft","domain":"ubisoft.com","url":"https://alion.io/company/ubisoft","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":75,"open_postings":28,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":35,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Backend","role_family":"Backend","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Montreal, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":79000,"max_usd":136000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":69},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenSearch","optional":false},{"name":"Pipeline as Code","optional":false},{"name":"PostgreSQL","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-07-28T15:08:04Z","employer_posted_date":"2026-07-28","last_verified_at":"2026-10-16T16:33:44Z","board_verified":true,"closed_at":null,"days_open":80,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":80},"description":"Quality Foundations (QF) develops and operates cross-functional products, platforms, and services that enhance the quality, observability, performance, and operations of Ubisoft games through data, analytics, and artificial intelligence. In this context, the Lead Data Technical plays a key role in defining and evolving the data foundations that support QF’s various products.\nThe incumbent serves as the primary technical authority for all matters related to data, data architectures, and analytics platforms within Quality Foundations. They act as the lead expert responsible for designing, evolving, and operating robust, scalable, and high-performance data solutions that meet the needs of development, production, analytics, and AI teams.\nWorking closely with architects, development teams, and product leaders, this role contributes to defining, implementing, and evolving the organization’s target data architecture. The incumbent ensures the adoption of technical best practices, promotes consistency across the Quality Foundations product portfolio, and aligns data initiatives with the company’s strategic objectives.\n What you'll do\nCollaborate with architects and contribute to the design of new data products and services by proposing robust, scalable solutions aligned with organizational needs.\nParticipate in the implementation of the target data architecture and drive its adoption across teams.\nServe as the subject matter expert for all topics related to data, data architectures, and data processing pipelines.\nProvide technical leadership and expertise across all Quality Foundations products regarding data storage, modeling, governance, and processing.\nDefine, maintain, and promote data standards and best practices within QF, ensuring their consistent application across teams.\nPropose, review, and validate technical and architectural decisions through Architecture Decision Records (ADRs), and ensure adoption of approved decisions.\nActively contribute to the development and delivery of initiatives involving the highest levels of complexity or risk.\nAdvise architects, project managers, and leaders on technology directions and opportunities to improve data platforms.\nAnalyze and optimize the performance, cost efficiency, reliability, and scalability of data systems.\nAct as a subject matter expert in relational and non-relational database optimization.\nCollaborate with development, analytics, artificial intelligence, and operations teams to ensure seamless integration of data solutions.\nEnsure the technical quality of data pipelines and promote best practices in monitoring, alerting, and operations.\nFoster knowledge sharing, mentorship, and the development of technical autonomy within data development teams.\nParticipate in the technical evaluation of new technologies, platforms, and data-related approaches.\nPerform any other related duties as required.\n What you'll bring to the team\nEducation :\nBachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or an equivalent field of study.\nRelevant Experience :\nMinimum of 8 years of experience in software development or data engineering.\nSignificant experience designing and implementing large-scale data platforms.\nExperience in technical leadership, team coaching, or mentorship.\nExperience with distributed architectures and large-scale data processing systems.\nSkills and Knowledge :\nTechnical Expertise\nStrong expertise in large-scale data solution development and SQL/NoSQL data modeling.\nStrong proficiency in one or more of the following languages: Python, PySpark, SQL, and Scala.\nSolid understanding of modern data architectures, data processing pipelines, and analytics platforms, including Medallion architectures (Bronze/Silver/Gold) and Lakehouse platforms (Databricks, Delta Lake).\nExperience designing configurable and environment-agnostic solutions (development, staging, production), including pipeline-as-code and configuration management practices.\nAbility to design scalable, high-performance, and maintainable solutions.\nExperience documenting architectural and technical decisions.\nTechnical Assets\nKnowledge of cloud services (AWS, Azure, or equivalent) as well as Docker and Kubernetes technologies.\nKnowledge of data orchestration frameworks such as Apache Airflow or Databricks Workflows.\nKnowledge of real-time data streaming technologies (Spark Structured Streaming or equivalent).\nKnowledge of Databricks, Apache Spark (batch and streaming), Delta Lake, Elasticsearch/OpenSearch, SQL Server, and PostgreSQL.\nKnowledge of large-scale data platform administration and both relational and non-relational databases.\nKnowledge of monitoring, logging, and alerting systems for data pipelines.\nUnderstanding of machine learning and artificial intelligence concepts.\nExperience working in high-volume, real-time critical systems environments (telemetry, observability, monitoring) is considered a significant asset.\nProfessional Competencies\nExcellent analytical and problem-solving skills.\nStrong ability to solve complex technical challenges.\nAptitude for mentoring and fostering technical autonomy within teams.\nStrong appreciation for configuration-driven approaches, including parameterized systems, declarative pipelines, and reproducible deployments (Infrastructure as Code).\nExcellent communication skills and ability to explain complex technical concepts to diverse audiences.\nInfluential leadership and the ability to drive adoption of best practices across teams.\nAbility to work effectively in a multidisciplinary environment.\nStrong initiative and autonomy.\nResults-oriented mindset with a focus on continuous improvement.\nAbility to manage multiple priorities simultaneously and make sound prioritization 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