Data Modeller

This role is hybrid and requires you to be at a Client office (160 Front Street W Toronto) at a minimum 4 days per week subject to change at any time.

We are seeking a Senior Data Modeller / Data Product Designer to join our Enterprise Payments team. This role will be responsible for designing end-to-end data structures across our Payments data ecosystem from MongoDB-based operational data stores through to Azure Databricks curated data products.

The successful candidate will play a key role in defining how Payments data is modelled governed shared and consumed across operational and analytical platforms. This position is ideal for someone who has deep expertise in data modelling and data product design and enjoys collaborating with business and technology partners to deliver scalable reusable and well-governed data solutions.

This role consists of approximately 75% data modelling and data product design and 25% data engineering enablement.

Design JSON schemas for MongoDB-based operational data stores aligned with business processes query patterns and schema evolution requirements.
Design and maintain Databricks/Delta Lake schemas that support curated and reusable data products.
Develop reusable Payments data products across individual payment domains and enterprise-wide payment views.
Design and evolve a Payments context layer and canonical data model to support analytics reporting and downstream data consumption.
Translate business requirements into logical and physical data models for operational and analytical use cases.
Support schema versioning migration strategies backward compatibility and ongoing model evolution.
Design data products aligned with governance standards metadata requirements discoverability and access controls within Unity Catalog or similar platforms.
Define and differentiate source-aligned domain-aligned and consumer-aligned data products.
Collaborate with business analysts architects data engineers and other stakeholders to operationalize data models through ingestion transformation and curation pipelines.
Support data governance initiatives including metadata management data quality lineage documentation and access management.
Create clear and comprehensive documentation to ensure data assets are reusable understandable and fit for purpose.

8 years of experience in data modelling across operational and analytical environments.
Strong experience designing JSON and semi-structured data models particularly within MongoDB or similar document-based databases.
Strong experience designing relational analytical or lakehouse schemas using SQL-based platforms.
Proven ability to translate business workflows requirements and query patterns into scalable maintainable data models.
Experience supporting schema evolution versioning migration and backward compatibility strategies.
Experience designing reusable datasets data products or data domains for analytics reporting APIs or enterprise consumption.
Strong understanding of data product principles including ownership usability discoverability documentation and consumer alignment.
Working knowledge of Databricks and Delta Lake schema design including performance and partitioning considerations.
Familiarity with Unity Catalog or equivalent metadata and governance frameworks.
Advanced SQL skills.
Strong stakeholder management communication analytical thinking and problem-solving abilities.
Experience collaborating with cross-functional teams including business stakeholders business analysts architects and engineers.

Experience working within the Payments domain.
Familiarity with ISO 20022 payment messaging standards and schema structures.
Experience designing canonical data models or enterprise context layers spanning multiple source systems.
Knowledge of MongoDB indexing sharding performance tuning and MongoDB Atlas.
Experience with PySpark Spark SQL Delta Lake optimization and Databricks performance best practices.
Experience with Azure Databricks Azure Data Factory Azure Synapse or similar cloud-based data platforms.
Understanding of event-driven architectures Kafka schema registries and streaming data patterns.
Familiarity with data governance practices including metadata management lineage privacy requirements audit controls and regulated data environments.
Experience with Collibra or similar data catalog and governance tools.

CGI is providing a reasonable estimate of the pay range for this role. The determination of this range includes factors such as skill set level geographic market experience and training and licenses and certifications. Compensation decisions depend on the facts and circumstances of each case. A reasonable estimate of the current range is $95000$145000. This role is an existing vacancy.

#LI-AV1!

• Financial Services
• JSON Web Token (JWT)
• Microsoft Azure Databricks
• SQL
• Unity
• MongoDB

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Life at CGI is rooted in ownership teamwork respect and belonging. Here youll reach your full potential because

You are invited to be an owner from day 1 as we work together to bring our Dream to life. Thats why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our companys strategy and direction.

Your work creates value. Youll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas embrace new opportunities and benefit from expansive industry and technology expertise.

Youll shape your career by joining a company built to grow and last. Youll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons.

At CGI we value the strength that diversity brings and are committed to fostering a workplace where everyone belongs. We collaborate with our clients to build more inclusive communities and empower all CGI partners to thrive. As an equal-opportunity employer being able to perform your best during the recruitment process is important to us. If you require an accommodation please inform your recruiter.

That same commitment to fairness extends to how we use technology. To support our recruitment team AI tools may be used to help assess applications though they never replace human judgement. All hiring decisions remain entirely in the hands of our recruitment professionals.

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