Company Description
Ubisoft is a global leader in gaming with teams across the world creating original and memorable gaming experiences, from Assassin’s Creed, Rainbow Six to Just Dance and more. We believe diverse perspectives help both players and teams thrive. If you’re passionate about innovation and pushing entertainment boundaries, join our journey and help create the unknown!
Job Description
The person in this role works closely with the Business Solutions Architect, application teams, and business stakeholders to deliver data and artificial intelligence solutions that make processes and systems smarter.
They develop and maintain data pipelines that meet the requirements of predictive models and design AI agents, including those built with Microsoft Copilot Studio, capable of leveraging data securely and efficiently.
The incumbent is also accountable for the accessibility, integrity, and quality of the required datasets.
What You'll Do
- Lead the design, implementation, and maintenance of data transportation processes required by Data Scientists.
- Perform data transformation operations to support predictive models.
- Design and maintain data architectures that ensure reliable pipelines for both structured and unstructured data.
- Design scalable data models required for the development of predictive models.
- Ensure seamless integration between data pipelines and data models.
- Integrate predictive models and AI solutions into applications, systems, and business operations.
- Design, develop, deploy, and maintain artificial intelligence agents using Microsoft Copilot Studio.
- Integrate AI agents with data pipelines, APIs, and existing systems.
- Collaborate with business teams to define use cases, conversational flows, and operating rules for AI agents.
- Monitor and ensure data quality (reliability, consistency, and integrity) as well as data flow performance.
- Track the performance of data pipelines, AI agents, and infrastructure, and recommend necessary improvements.
- Utilize distributed computing technologies for model training and deployment.
- Contribute to a variety of projects involving the implementation of innovative systems, solutions, and processes.
- Perform other related duties as required.
Qualifications
Education
- University degree in Computer Science, Engineering, or a related field.
Relevant Experience
- Minimum of 5 years of industry experience in development, coding, scripting, and data-oriented design.
- Minimum of 5 years of experience in developing and administering large-scale data environments.
- Minimum of 3 years of experience in data modeling and SQL/NoSQL database administration.
- Hands-on experience developing or integrating AI solutions or intelligent agents is considered a strong asset.
Skills
- Ability to design processes based on data flow concepts and architectures.
- Ability to perform data extraction, transformation, and loading (ETL/ELT).
- Ability to configure, use, and develop data management systems.
- Ability to develop large-scale, structured software using software engineering best practices.
- Ability to use various tools and programming languages (e.g., Python, SQL, Bash) to integrate systems.
- Ability to design and maintain AI agents and conversational workflows.
- Creative thinking and strong problem-solving skills.
- Team-oriented mindset with excellent interpersonal and communication skills.
- Strong focus on delivering strategic business value.
- Good understanding of Machine Learning and Generative AI.
- Ability to work independently and solve complex problems.
- Knowledge of Agile methodologies.
Knowledge & Technical Expertise
- Experience with Flume, NiFi, Kafka, or other data pipeline technologies.
- Experience with REST APIs.
- Experience with Microsoft Copilot Studio, Power Platform, or similar AI agent platforms.
- Experience with C# and .NET.
- Experience working in Linux and Windows environments.
- Strong understanding of computer science fundamentals, including algorithms and data structures.
- Knowledge of data-centric architectures and data flow principles.
- Experience with data quality, integrity, cleansing, and transportation processes.
