data mining analyst

TD Bank; Toronto; On-site; CAD 76,000 - 116,000; Full time

Job summary

A leading financial institution in Toronto is seeking a Data Engineer II to design and maintain scalable data pipelines. The role involves collaboration with various teams to ensure data quality and develop technical solutions. Ideal candidates will have experience in ETL processes and the ability to communicate complex information clearly. This position offers competitive compensation within the range of $76,800 to $115,200 CAD per year.

Qualifications

• Experience in designing and maintaining data pipelines and ETL processes.
• Strong analytical skills for data quality and integrity.
• Ability to articulate complex technical designs to non-technical partners.

Responsibilities

• Design, build, and maintain scalable data pipelines.
• Collaborate with business partners for technical solutions.
• Ensure data quality and governance.

Skills

Data pipeline development

ETL processes

Data analysis

Data governance

Tools

Industry standard modeling tools

Standard ETL tools

Job description

Job Details

Title: Data Engineer II at TD Bank

Posted on October 26, 2025.

Location: Toronto, Ontario, Canada. Work location: On site. Hours: 37.5.

Line of Business: Technology Solutions.

Pay: $76,800 - $115,200 CAD per year.

TD is committed to providing fair and equitable compensation opportunities to all colleagues.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL processes to support TBSM data needs.
• Collaborate with business partners to understand data requirements and translate them into technical solutions.
• Ensure data quality, integrity, and governance across systems and platforms.
• Troubleshoot and resolve production issues in a timely and proactive manner.
• Work closely with cross‑functional teams including business analysts, data scientists, and application developers.
• Contribute to the continuous improvement of data engineering practices, tools, and standards.
• Stay current with industry trends and emerging technologies to recommend innovative solutions.
• Perform data analysis and assess data management requirements for a specific platform or journey, including complex analysis involving multiple pods or products.
• Maintain expert knowledge of upstream data, including knowledge provided through data profiling, data quality reporting, and production of metadata.
• Support the acquisition and ingestion of data.
• Articulate complex, large‑scale, and high‑impact technical designs and development details to non‑technical business partners.
• Elicit, analyze, and understand business and data requirements to develop complete business solutions, including data models (entity relationship diagrams, dimensional data models), ETL and business rules, data life‑cycle management, governance, lineage, and metadata.
• Ensure data is maintained in compliance with enterprise data standards, policies, and guidelines.
• Develop and maintain complex data models using industry standard modeling tools.
• Develop and maintain complex ETL jobs and frameworks using the bank's standard tools.
• Provide support to the development and testing teams to resolve data issues, including escalation support on complex issues.
• Support partners and stakeholders in interpreting and analyzing data.
• Build effective working relationships within own pod and across partner teams to encourage collaboration on all pod deliverables.
• Coordinate with technology work teams such as ITS, ARE, Architecture, Enterprise Protect, etc., to ensure overall delivery success.
• Support the QA team with data analysis/investigations of complex issues/test cases as part of SIT/UAT/PAT testing.
• Provide oversight on post‑implementation activities during the warranty period.
• Execute and approve code check‑in/check‑out into source code repository as part of source code management.
• Work closely with ITS/ARE teams to support code packaging and deployment (CI & CD).

Advertised Until

2025-11-24