Senior Data Modeller & Product Designer, Payments

The Toronto-Dominion Bank (Canada)

Toronto

On-site

CAD 105,000 - 129,000

Full time

4 days ago

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Benefits offered by this job

Discretionary variable compensation

Growth opportunities

Training and development

Job summary

The Toronto-Dominion Bank (Canada) is seeking a Senior Data Modeller / Data Product Designer for the Enterprise Payments data ecosystem. You will design end-to-end data structures from MongoDB ODS to Azure Databricks curated products, focusing on schema design and context-layer modelling.

The role is ~75% data modelling / data product design and ~25% data engineering enablement, partnering with analysts, engineers, architects, and Payments partners to build reusable data products and governance

Qualifications

8+ years of experience in data modelling across operational and analytical platforms.
Strong experience designing JSON / semi-structured schemas, preferably for MongoDB or similar document databases.
Strong experience designing SQL / analytical schemas for data platforms, warehouses, or lakehouses.
Experience translating business workflows and query patterns into durable, scalable schema designs.
Experience with schema evolution, versioning, backward compatibility, and migration strategies.
Experience designing reusable datasets or data products for analytics, reporting, APIs, or downstream consumers.

Responsibilities

Design JSON schemas for MongoDB-based transactional ODS capabilities, aligned to business workflows, query patterns, and schema evolution needs.
Design corresponding Databricks/Delta table schemas for curated, reusable data products.
Define reusable Payments data products across individual payment types and combined cross-payment views.
Design a context layer / canonical Payments model that supports cross-product analytics, reporting, and downstream consumption.
Translate business requirements into logical and physical data models for both operational and analytical use cases.
Support schema evolution, versioning, migration, and backward compatibility across MongoDB and Databricks.
Design data products aligned to Unity Catalog structures, access patterns, discoverability, and governed sharing.
Differentiate between source-aligned, domain-aligned, and consumer-aligned data products.
Collaborate with data engineering teams to operationalize models through ingestion, curation, and transformation pipelines.
Support governance expectations including metadata, data quality, lineage, access controls, and appropriate documentation.
Work with business and technology partners to ensure data products are understandable, reusable, and fit for consumption.