Overview
IT Data Specialist Jobs in Toronto, Canada at TD
Title: IT Data Specialist
Company: TD
Location: Toronto, Canada
Category:
Work Location
Toronto, Ontario, Canada
Hours
37.5
Line of Business
Technology Solutions
Pay Details
$114,000 – $136,800 CAD
Department Overview
Residing within Enterprise Protect organization, the Financial Crime & Risk Management (FCRM) Technology team is responsible for the delivery and support of technology solutions for the respective FCRM business unit. Given the ongoing pace of regulatory change and ongoing importance of risk management, this is a fast-growing area within the bank translating into considerable demand and growth within its technology teams.
About
this Role
We are looking for an IT Data Specialist for our Financial Crime & Risk Management systems (Oracle – Transaction Monitoring and Customer Risk Rating solutions). You will have the opportunity to engage in cross team initiatives beyond your immediate project to modernize the technology and capabilities to align with the portfolio and enterprise technology roadmaps.
The primary responsibility of our team is to design, develop and maintain the technology platform that processes the bank’s payments through behaviour detection algorithms to detect suspicious and fraudulent activity.
Responsibilities
Meaningful work is fueled by meaningful performance and career development conversations with your manager.
- Design, develop and implement data controls and develop processes to ensure data integrity from source to target is met, i.e., ensuring data sourced meets the data quality standards designed.
- Lead data initiatives within the FCRM Technology which require extensive collaboration with multiple Business & Technology teams globally to comprehend business requirements, develop respective functional specifications and detailed solution plan to execute these data initiatives.
- Troubleshoot database and data pipeline issues efficiently.
- Independently, perform data profiling, root cause analysis, and analyze Source to Target Mappings documents/data dictionaries to identify root cause of data issues and assist with implementing solutions post alignment with Business and Technology stakeholders.
- Lead triage meetings globally and collaborate with required stakeholders to determine fix for data issues identified.
- Automate manual data processing tasks and build scalable solutions.
- Independently assess and further improve existing documentation to ensure end-to-end processes performed by the team are captured for traceability purposes.
- Collaborate with teams to integrate databases with applications and analytics platforms.
- Collaborate with the Technology development and testing teams to ensure all data transformation logics are adequately developed and tested across lower environments.
- Leverage analytical tools and develop required metrics to measure the quality of data obtained across source systems.
- Foster an environment and culture that encourages productivity, innovation, process improvement, teamwork, and a high level of professionalism.
Qualifications
What can you bring to TD?
- University degree, preferably in technology/ data engineering
- Minimum of 8
-10 years of AML transaction monitoring experience, preferably with large banks - Minimum of 8 years of experience in data management (Hands‑on experience in data profiling, designing, and developing data controls / Data quality rules across the data pipeline, Developing, and analyzing Source to Target mapping documents, Performing root cause analysis across data issues)
- Minimum of 8 – 10 years of experience in PL/SQL, including query optimization, stored procedures, and indexing (Preferably in Oracle based tools)
- Proven ability to run complex analytical queries directly against Azure Data Lake Storage (ADLS) using distributed query engines such as Azure Synapse Serverless SQL, Databricks SQL etc.
- Hands‑on experience reading, writing, and transforming data in ADLS using PySpark, Pandas or Polars to perform data wrangling at scale.
- Experience with relational databases (PostgreSQL, MySQL, SQL Server, Oracle) and No
SQL databases (MongoDB, Redis, etc.)
- Excellent understanding of payments and data coming from settlement systems including the flow of funds, payment messaging formats such as Swift and systems such as ACH,…