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The Analyst, AI will drive and support the evolution of the use of modern data platforms in the context of Artificial Intelligence (AI) solutions helping the organization to satisfy the needs of agility and strategic business growth. They will implement data models, associated data pipelines, and build other software components that enable stakeholders to analyze and develop strategic insights that can help make effective decisions and drive growth of the organization.
In this role, you will join the AI-CoE (Center of Excellence), a central group within Air Canada's IT organization that builds Machine Learning and Optimization solutions to internal business units including Revenue Management, Network Planning, Operations, Maintenance, and Cargo organizations.
This position will report to the Director, Artificial IntelligenceFunctional Accountabilities
- Conceptualize and architecture cloud distributed data solutions in context of AI projects with an orientation on PaaS.
- Design, implement, deploy, test, and maintain solutions and large-scale processing systems.
- Undertake and analyze data to determine patterns and insights that can optimize data ingestion and data presentation.
- Support the delivery of AI projects in designing and implementing the data pipelines/data streaming. Design and develop processing pipelines that ingest data into a data lake.
- Design and develop scalable ETL pipelines using multiple sources of data in various formats between data lake and data warehouse.
- Collaborate with data scientists on preparing the data needed to implement AI models in accordance with project requirements and AI data engineering standards.
- Develop, construct, test and maintain architectures, such as databases and large-scale processing systems.
- Recommend and implement ways to improve data reliability, efficiency, and quality.
- Develop datasets and databases with machine learning tools to solve real time business problems.
- Educate the organization both from IT (including external partners) and the business perspectives on data ingestion and data streaming tools, processes, and best practices.
- Support the maturation of AI platforms, modules, and services that address cross-enterprise opportunities through market research and proof-of-concepts.
- Establish strong relationship with external partners to ensure strong delivery, innovation and ongoing improvement in receiving high value services.
- Develop and improve processes for data modeling, mining, and production.
- Collaborate with stakeholders including the Product owner, data science, and design teams to assist with data-related technical issues, support their data infrastructure needs, and identify opportunities for improvements.
- Translate business needs into technical requirements.
- Provide technology or services ownership direction on all matters related to a key functional area - to associated functional lead and peers.
- Provide technology specific financial inputs related to both data engineering tool set costs and monthly data consumption costs.
- Responsible for working with stakeholders related to a key functional area to ensure synergistic collaboration and attain shared goals.
- Responsible for ensuring consistency of data engineering tools and processes across projects/products.
- Provide business and technical inputs to Business Governance and Operational Management Committees, as appropriate.
- Responsible for handling high amount of technology complexity and drive autonomous decision making, as it relates to adoption of technology best practices.
Conditions of Employment:
- A relevant University degree/technical certification, and/or relevant experience commensurate to the role.
- 3-5 years of software engineering experience with a minimum of 1 year working with modern data platforms and cloud technology as a data engineer collaborating on the development and implementation of machine Learning models.
- Familiarity and/or strong interest in machine learning, statistical models, and AI.
- Strong background in cloud computing services like Microsoft Azure.
- Experience with real-time messaging systems (pub/sub, Kafka).
- Experience with writing automated and functional tests.
- Experience in feature engineering.
- Excellent business acumen and communication skills.
- Forward Thinking - Anticipating the implications and consequences of situations and taking appropriate action to be prepared for possible contingencies.
- Analytical Thinking - Approaching a problem by using a logical, systematic, sequential approach.
- Demonstrate significant technical depth to handle strategic technology priorities.
- Proficiency in (or in similar) technologies:
- Relational databases like SQL Server and non-relational databases like Cosmos.
- Python programming skills with good OOP, functional and/or analytical experience.
- Azure Databricks, Data Lake Store, Data Factory.
- Spark, including Delta Lake architecture principles to handle both batch and streaming data ingestion scenarios.
- Candidates must be eligible to work in the country of interest, at the time any offer of employment is made and seeking any required work permits/visas or other authorizations which may be required is the sole responsibility of the candidates applying for this position.
Based on equal qualifications, preference will be given to bilingual candidates.Diversity and Inclusion
Air Canada is strongly committed to Diversity and Inclusion and aims to create a healthy, accessible and rewarding work environment which highlights employees' unique contributions to our company's success.
As an equal opportunity employer, we welcome applications from all to help us build a diverse workforce which reflects the diversity of our customers, and communities, in which we live and serve.Air Canada thanks all candidates for their interest; however only those selected to continue in the process will be contacted.