Data Engineer II

Perform data analysis and assess data management requirements.,Maintain expert knowledge of upstream data, including data profiling, quality reporting, and metadata.,Support the acquisition and ingestion of data.,Articulate complex technical designs to non-technical business partners.,Elicit, analyze, and understand business and data requirements to develop complete business solutions (data models, ETL, business rules, data life-cycle management, governance, lineage, and metadata).,Ensure data 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 development and testing teams for data issue resolution.,Support partners and stakeholders in interpreting and analyzing data.,Build effective working relationships within own pod and across partner teams.,Coordinate with technology work teams (ITS, ARE, Architecture, Enterprise Protect) for delivery success.,Support QA team with data analysis/investigations during SIT/UAT/PAT testing.,Provide oversight on post-implementation activities.,Execute & approve code check-in/check-out into source code repository.,Work closely with ITS/ARE teams for code packaging & deployment (CI & CD).,Lead participant in design & architecture reviews.,Raise service-now requests and work with change management for release management.,Lead data engineering initiatives and capabilities, data governance principles.,Ensure metadata and data lineage capture compatible with enterprise tools.,Adhere to standard security coding practices.,Identify, document, and implement enhancements for technical decisions, risks, and lessons learned.,Protect organizational interests, manage risks, and escalate high-risk activities.,Adhere to internal policies/procedures and regulatory guidelines.,Keep current on emerging trends/developments.,Enable team members by sharing knowledge and leveraging engineering best practices.

Advanced knowledge of data engineering frameworks, technologies, tools, processes, patterns, and procedures.,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.

Degree, Postgraduate Degree, or Technical Certificate in Data Management or related discipline (e.g., Computer Science, Engineering), or equivalent practical experience.