Data Engineer II (US)

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.  As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

The Data Engineer II provides a broad range of data engineering functions including data modeling, data quality, data profiling, data acquisition and ingestion, extract transform load (ETL), metadata enrichment and management, data provenance and lineage, and other specialized data management functions. Depth & Scope: 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 Education & Experience: Degree, Postgraduate Degree, or Technical Certificate in Data Management or related discipline (e.g. Computer Science, Engineering), or equivalent practical experience 3+ years of relevant experience Customer Accountabilities: Performs data analysis and assesses data management requirements for a specific Platform or Journey, including complex analysis involving multiple pods or products Maintains expert knowledge of upstream data, including knowledge provided through data profiling, data quality reporting, and via the production of metadata Supports the acquisition and ingestion of data Articulates complex, large scale, and high impact technical design and development details to non-technical business partners Elicits, analyzes, and understands 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 Ensures data is maintained in compliance with enterprise data standards, policies, and guidelines Develops and maintains complex data models using industry standard modeling tools Develops and maintains complex ETL jobs and frameworks using the Bank's standard tools Provides support to the development and testing teams to resolve data issues, including escalation support on complex issues Supports partners and stakeholders in interpreting and analyzing data Builds effective working relationships within own pod and across partner teams to encourage collaboration on all pod deliverables Shareholder Accountabilities: Coordinates with technology work teams such as ITS, ARE, Architecture, Enterprise Protect etc. to ensure overall delivery success Supports the QA team with data analysis/investigations of complex issues/ test cases as part of SIT/UAT/PAT testing Provides oversight on post implementation activities during the warranty period Executes & approves code check-in/ check-out into source code repository as part of source