Job Title: Senior AI Data Engineer Job Location: Toronto, ON, Canada (Hybrid - 4 Days Onsite, 1 Day Remote) Position Type: Contract (6+ Months) Important Note: Prior banking client experience is mandatory.

Please do not apply with Data Scientist profiles (this is strictly a data engineering/Fin

Ops role).

The selection process includes an AI screening interview.

Job Overview We are seeking an experienced Sr. AI Data Platform Engineer with a strong background in Fin

Ops data reporting to join our client, TD Bank, in Toronto.

In this role, you will build and maintain Fin

Ops data pipelines from ingestion through reporting, integrating technology and financial data to support cloud cost management, chargeback/showback models, forecasting, and TCO optimization.

Key Responsibilities Build and maintain scalable Fin

Ops data pipelines for ingestion, transformation, and self-service analytics.

Normalize cloud and technology spend data across provider feeds, aligning with standards like FOCUS.

Integrate billing, usage, tagging, metadata, CMDB, finance, and vendor data across enterprise systems.

Create trusted datasets and dashboards for cost reporting by business unit, product, application, and environment.

Build analytics to support budget guardrails, variance reporting, anomaly detection, and optimization workflows.





Develop reporting for rightsizing, idle resource cleanup, license reclamation, and commitment-based spend (reservations/savings plans).

Ensure strict data quality, lineage, reconciliation, controls, and auditability across all Fin

Ops data assets.

Required Skills & Experience 8 10 years of qualified experience in data engineering, analytics engineering, BI engineering, or financial data analytics.

Mandatory prior experience working with banking or major financial services clients.

Strong expertise in SQL , relational databases, and advanced data modeling / schemas .

Proficiency in Python for automation, API/telemetry ingestion, and pipeline scripting.

Strong hands-on experience building complex ETL/ELT pipelines and working with large datasets.

Experience with cloud data platforms (e.g., Databricks, Snowflake, Big

Query, Azure Synapse, Microsoft Fabric).

Experience with BI and reporting tools (e.g., Power BI, Tableau, Looker).

Strong understanding of financial data analytics, cloud spend tracking, and Fin

Ops frameworks.

How to Apply: If you match these requirements with verified banking experience and are ready for an exciting hybrid opportunity in Toronto, send your updated resume directly to .

📌 AI Data Engineer (Ontario)
🏢 Talent Portus
📍 Ontario