Software Engineer III

Role overview

Engineering and delivery

• Lead end-to-end solution architecture and delivery, align stakeholders, own execution, and ensure production readiness.
• Build critical components, resolve bottlenecks, and modernize systems using incremental, de-risked migration strategies.
• Define and validate non-functional requirements, automate delivery, manage dependencies, and improve performance, availability, resilience, and cost efficiency.
• Lead cloud architecture decisions across environments, selecting scalable infrastructure, deployment models, and integration approaches.
• Deliver predictable design-to-operation outcomes with documented architecture decisions aligned to enterprise standards.

AI workflow and governance

• Champion AI-assisted development using copilots and LLM agents while maintaining enterprise standards.
• Establish AI guardrails covering approved use cases, prompt patterns, code provenance, and documentation.
• Implement validation pipelines for generated code, including testing, security scans, dependency checks, secret detection, and architectural rules.
• Define human review, code-review, threat-modeling, and design-review requirements for high-risk changes.
• Promote responsible AI use and establish repeatable workflows for generation, verification, refactoring, and documentation.

Quality, operations, and team leadership

• Ensure governance, compliance, and risk alignment; lead design and code reviews, release readiness, and operational gating.
• Optimize performance and cost, apply FinOps practices, and drive remediation and continuous improvement.
• Create reusable patterns, reference implementations, and documentation; mentor engineers, unblock complex issues, and share knowledge.
• Promote a high-performing, inclusive team, communicate risks, and support hiring and onboarding.

Technical qualifications

• Exceptional problem-solving and experience diagnosing complex system failures and designing resilient solutions.
• Hands-on normalized, extensible relational data modeling, including schemas, entities, relationships, keys, constraints, and versioned data.
• Hands-on knowledge graph or graph database modeling and implementation, graph traversal and queries, and integration with PostgreSQL or graph databases.
• Strong PostgreSQL, SQL, Python, and data engineering experience, including indexing, query optimization, JSON/JSONB, transformations, and high-volume processing.
• Experience with REST/Graph APIs, batch/file processing, Kafka or event-driven integration, incremental processing, and SQL versus NoSQL trade-offs.
• Ability to contribute to a scalable data lake with raw, standardized, and curated layers.
• Advanced CI/CD and DevOps, automated testing, release strategies, infrastructure as code, and environment management.
• Expert cloud infrastructure and scalable architecture knowledge, including cloud-native services, containers, resiliency, observability, and secure deployment.
• Ability to troubleshoot data discrepancies, missing or duplicate records, schema changes, ingestion failures, performance, and reconciliation issues.
• Experience designing curated datasets, APIs, scheduled extracts, and event-based interfaces for downstream users.
• Practical coding copilot or LLM-agent experience and a vision for safe enterprise use.
• Undergraduate or postgraduate degree, or technical certificate; 5–7+ years of relevant experience. Graduate degree is a plus.

Preferred qualifications

• Preferred core technologies include PostgreSQL, SQL, Python, REST/Graph APIs, Kafka, batch/file processing, Azure, Databricks/PySpark, Git, CI/CD, and graph databases.
• Data management, governance, cataloging, or metadata platform experience is a plus; DataHub, OpenMetadata, Collibra, or comparable platforms are preferred.
• Knowledge of lineage and provenance, including OpenLineage, W3C PROV-oriented models, and automated lineage capture, is preferred.
• Exposure to Elasticsearch or OpenSearch and Kafka or comparable message queues is preferred.
• Practical security knowledge such as RBAC, ABAC, SSO/MFA, secrets management, audit logging, access governance, network controls, and secure configuration is preferred.
• Pandas experience and cloud experience across Azure, AWS, or hybrid environments are advantageous.
• Familiarity with responsible coding copilots or AI-assisted developer workflows is preferred.

Compensation

• Pay range is CAD $125,500–$154,000 and reflects a temporary market premium reassessed annually; the posting does not specify a pay cadence.

About TD