Job Title

Overview We are seeking a highly skilled and motivated Data Engineer II to join our dynamic team supporting the Treasury & Balance Sheet Management (TBSM) business. This role is critical to the development and delivery of data solutions that enable strategic decision-making across key banking products such as deposit accounts, mortgages, and more. The ideal candidate will bring a strong blend of technical expertise and business acumen, with a proven ability to manage complex production issues, communicate effectively across teams, and adapt to evolving project requirements and technologies. Location: Toronto, Ontario, Canada Hours: 37.5 per week Key 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. CUSTOMER 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 via the production of metadata. Support the acquisition and ingestion of data. Articulate complex, large scale, and high impact technical design 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. SHAREHOLDER 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 & 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 & deployment (CI & CD) into higher environments. Be the lead participant in the design & architecture reviews or the application. Raise service-now requests and work with the change management team to support release management activities. Lead data engineering initiatives and capabilities, data governance principles and how they apply across the organization. Ensure metadata and data lineage is captured and compatible with enterprise metadata and data management tools and processes. Adhere to standard security coding practices to ensure the application is free of most common coding vulnerabilities. Ensure technical decisions, technical risks and lessons learned are identified, clearly documented and enhancements are accordingly implemented. Protect the interests of the organization identify and manage risks, and escalate non-standard, high-risk activities as necessary. Adhere to internal policies/procedures and applicable regulatory guidelines. Keep current on emerging trends/developments and grow knowledge of the business, related tools, and techniques. Enable team members by sharing knowledge and leveraging engineering best practices. EMPLOYEE / TEAM Participate fully as a member of the team, support a positive work environment that promotes service to the business, quality, innovation and teamwork and ensure timely communication of issues/ points of interest. Provide thought leadership and/or industry knowledge for data engineering best practices and participate in knowledge transfer within the team and business unit. Keep current on emerging trends/developments and grow knowledge of the business, related tools and techniques. Participate in personal performance management and development activities, including cross training within own team. Keep others informed about status/progress of projects and day-to-day activities. Mentor and enable team members by sharing knowledge and leveraging engineering best practices. Support the team by providing guidance and proactively identifying and resolving issues. Lead, motivate and develop relationships with internal and external partners/stakeholders. Contribute to a fair, positive and equitable environment that supports a diverse workforce. Act as a brand ambassador for your business area/function and the bank, both internally and/or externally. BREADTH & DEPTH Advanced knowledge of data engineering frameworks, technologies, tools, processes, patterns, and procedures, including how they impact other technology areas such as Architecture or Infrastructure. Performs complex technical tasks independently. Advanced knowledge of TD applications, systems, networks, innovation, design activities, business, organization, best practices, and standards. Designs and develops to meet business and technical requirements; analyzes, adapts, integrates, codes, tests, debugs, and executes. Uses and evolves established patterns to solve complex problems; leads the development of new patterns where necessary. May be recognized as a subject matter expert in areas directly related to key accountabilities. Generally reports to a Practice Lead. Experience And / Or Education Degree, Postgraduate Degree, or Technical Certificate in Data Management or related discipline (e.g. Computer Science, Engineering), or equivalent practical experience. 3-5 years of relevant experience. Proficiency in SQL, Python, or Scala for data manipulation and pipeline development. Experience with big data technologies (e.g., Hadoop, Spark, Databricks, Snowflake). Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and data warehousing solutions. Strong understanding of data modeling, normalization, and performance optimization. #J-18808-Ljbffr