Sr. IT Data Analyst

Role overview

Responsibilities

• Design and implement source-to-target data controls and processes to meet data quality standards.
• Lead data initiatives and translate business requirements into functional specifications and detailed solution plans.
• Troubleshoot databases and data pipelines; profile data and investigate root causes using mappings and data dictionaries.
• Lead global triage meetings and coordinate with stakeholders on data fixes.
• Automate manual data processing and develop scalable solutions.
• Improve end-to-end process documentation for traceability.
• Integrate databases with applications and analytics platforms.
• Coordinate with development and testing teams to validate data transformation logic in lower environments.
• Develop metrics and analytical tools to measure source-system data quality.
• Maintain governance processes and document data quality controls, business logic validations, and feed checks.

Experience and qualifications

• University degree, preferably in technology or data engineering.
• 5–7 years of AML transaction monitoring experience; large-bank experience is preferred.
• At least 5 years of data management experience, including profiling, data controls, data quality rules, mapping, and root cause analysis.
• 8–10 years of PL/SQL experience including query optimization, stored procedures, and indexing; Oracle-based tools are preferred.
• Ability to query ADLS using distributed query engines such as Azure Synapse Serverless SQL or Databricks SQL.
• Hands-on ADLS data wrangling at scale using PySpark, Pandas, or Polars.
• Experience with relational databases including PostgreSQL, MySQL, SQL Server, or Oracle, and NoSQL databases including MongoDB or Redis.
• Strong understanding of payments, settlement data, fund flows, and systems or formats such as SWIFT, ACH, and Fedwire.
• Comfort working across time zones, including overlap with Singapore and India teams.
• Strong relationship-building skills and ability to apply analytics to financial markets, regulation, and commercial value.
• The role description requests 8–10 years of experience leading complex data projects.

Technical and domain knowledge

• Data management, profiling, data quality controls, source-to-target mapping, and root cause analysis.
• PL/SQL, SQL optimization, stored procedures, and Python scripting.
• ADLS, distributed query engines, PySpark, Pandas, or Polars.
• Financial Crime and Risk Management systems, AML transaction monitoring, and payments and settlement systems.

Pay information

• The description provides a base-pay range of CAD $81,600–$115,200 but does not specify a compensation cadence.

Work location

• The description lists Toronto, Ontario, Canada as the work location.