Software Engineer III - Metadata Management & Data Discovery

Work Location: Toronto, Ontario, Canada

Hours: 37.5

Line of Business: Technology Solutions

Pay Details: $125,500 - $154,000 CAD The pay details posted reflect a temporary market premium specific to this role that is reassessed annually. 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  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.

We are seeking a highly technical Software Engineer III – Metadata Management & Data Discovery to help lead the design, engineering, and delivery of enterprise metadata harvesting capabilities across cloud, multi-cloud, and legacy on-premises data platforms.

This role will be responsible for ideating, designing, building, and operationalizing scalable metadata harvesting solutions that enable automated discovery, cataloging, lineage, classification, and governance of enterprise data assets. The successful candidate will support the Data Discovery and Metadata Harvesting function by building reusable patterns and integrations that harvest structured and semi-structured metadata from platforms such as Databricks Unity Catalog, Azure ADLS, Azure Synapse, Snowflake, AWS, Google Cloud, Oracle, SQL Server, DB2, Teradata, mainframe files, SFTP/network shares, and other enterprise data stores.

The role will be central to advancing Data Compass / Collibra as the enterprise metadata system of record and will partner closely with engineering, cloud infrastructure, architecture, security, governance, and data platform teams to ensure metadata is harvested, normalized, enriched, reconciled, and maintained in a trusted and audit-ready manner.

• Lead the technical design and implementation of enterprise metadata harvesting solutions across cloud, multi-cloud, and on-premises platforms.
• Build automated harvesting pipelines and connectors to capture technical, operational, business, lineage, classification, ownership, and stewardship metadata.
• Design reusable ingestion patterns using Collibra EDGE connectors, REST APIs, JDBC/ODBC, event-driven approaches, file-based ingestion, and custom adapters where needed.
• Engineer metadata harvesting solutions for Databricks Unity Catalog, including catalog, schema, table, view, column, permission, tag, lineage, and operational metadata extraction.
• Develop scalable harvesting patterns for Azure data platforms, including ADLS Gen2, Azure SQL, Synapse, Azure Data Factory, Key Vault, private endpoints, service principals, and secure connectivity.
• Extend metadata harvesting capabilities across Snowflake, AWS, Google Cloud, and major on-premises data stores.
• Design and implement reconciliation controls to compare source platform inventories against harvested assets in Data Compass / Collibra.
• Define and maintain asset mapping, attribute mapping, classification rules, lineage stitching logic, enrichment patterns, and metadata quality checks.
• Partner with cloud infrastructure, IAM, security, and networking teams to establish secure access patterns for harvesting across environments.
• Support environment promotion from DEV/SIT/PAT/PROD with proper controls, monitoring, alerting, logging, and operational readiness.
• Build monitoring and support capabilities for harvesting jobs, including failure alerts, retry logic, health checks, lineage validation, and incremental harvesting.
• Collaborate with governance and business teams to ensure metadata is complete, trusted, actionable, and aligned to enterprise data standards.
• Create technical documentation, architecture diagrams, implementation guides, runbooks, and reusable patterns for onboarding new…