Software Engineer II

Description

You will provide hands-on engineering expertise to build scalable, reliable and secure services for the data catalog platform.

The work spans several cloud environments, so you need practical knowledge of cloud infrastructure, deployment patterns and scalable engineering.

You turn architecture and product requirements into working software. You handle complex components on your own and work closely with senior engineers, Architecture, Security, Infrastructure and Product.

You own detailed design, build, testing and operational support in your assigned solution area, and help shape engineering standards, automation and reusable patterns.

The role includes responsible use of AI-assisted engineering, within approved guardrails and with generated output checked through review, testing and secure delivery.

The company is a large North American bank with more than 95,000 colleagues, serving over 27 million households and businesses in Canada, the United States and beyond.

You will report to a Senior Manager, Engineering.

The team contacts candidates it wants to interview and shares outcomes by email or phone.

Training and onboarding sessions are provided to help you settle into the role.

Responsibilities

• Write and maintain detailed solution designs, acting as the application subject matter expert and confirming alignment with Architecture.
• Build, test and support complex components, APIs, integrations and data flows that meet business, technical, performance and security needs.
• Build cloud-ready components using approved infrastructure, deployment and scaling patterns.
• Assess technical requirements and recommend practical engineering solutions for features, components and platform capabilities.
• Review deliverables during design and development to spot quality gaps, redesign needs and cross-release impacts.
• Work with technology partners to set metrics, check performance targets and fix data or application issues that affect solution integrity.
• Use approved AI coding tools for coding, refactoring, testing and documentation within enterprise guardrails.
• Check AI-generated code through peer review, automated tests, linting, dependency checks and secure coding practices before release.
• Record prompts, assumptions or generated artifacts when needed so outputs stay traceable.
• Raise privacy, IP, security or data-handling concerns before sensitive information enters AI-assisted workflows.
• Share examples and lessons that help the team use AI-enabled engineering safely.
• Follow enterprise frameworks and controls, run code reviews, and take part in operational readiness reviews and design sign-offs.
• Look for ways to improve quality, cut costs, automate manual work and improve the stakeholder experience.
• Identify and manage risks, and escalate non-standard or high-risk activities.
• Track emerging engineering trends, regulatory expectations and technology practices that could affect your solutions.
• Mentor team members by sharing knowledge, engineering practices and practical guidance.
• Keep others informed about project status, technical risks, issues and daily delivery details.
• Build productive working relationships with technology partners, product stakeholders and control functions.
• Help maintain a positive, equitable and collaborative team environment.
• Deliver complex features and components on time, in line with architecture direction and engineering standards.
• Document designs, implementation choices and trade-offs clearly enough for review, support and audit.
• Support monitoring, incident response and timely fixes for defects and production issues.

Requirements

• Strong problem-solving skills, with a record of diagnosing complex system failures and designing resilient solutions.
• Hands-on experience designing normalized, extensible relational data models, including schemas, entities, relationships, keys, constraints, versioned history, and models that handle multiple source structures.
• Hands-on experience designing knowledge graph or graph data models, including nodes, edges, relationship semantics, traversal and query patterns, and integrating graph capabilities with PostgreSQL or graph databases for discovery, lineage, dependency mapping and impact analysis.
• Strong hands-on experience with PostgreSQL, SQL, Python and data engineering, including schemas, indexing, query optimization, JSON/JSONB where suitable, transformations, change tracking and high-volume processing.
• Proven experience building reusable ingestion and extraction patterns across REST/Graph APIs, batch and file processing, Kafka or event-driven integration, and incremental processing, with an understanding of SQL versus NoSQL trade-offs.
• Hands-on ability to contribute to a data lake design and build, with raw, standardized or normalized, and curated or consumption layers that scale for new sources and use cases.
• Advanced CI/CD and DevOps practice, including automated testing, release strategies, infrastructure as code and environment management.
• Expert knowledge of cloud infrastructure and scalable architecture, including cloud-native services, containers, infrastructure as code, resiliency patterns, observability and secure enterprise deployment.
• Strong ability to investigate and resolve data discrepancies, missing or duplicate records, broken relationships, schema changes, ingestion failures, performance issues and source-to-target reconciliation problems, using suitable data-quality controls.
• Experience designing curated datasets, APIs, scheduled extracts and event-based interfaces that let downstream applications and users consume data.
• Practical experience with coding copilots or LLM agents, and a clear view of how to use them safely in enterprise workflows.
• Ability to own complex development work independently while guiding junior developers through design, development patterns, troubleshooting, code reviews, testing, documentation and knowledge sharing.
• Ability to explain constraints and trade-offs clearly to engineers, partners and leadership.
• An undergraduate degree, postgraduate degree or technical certificate.
• A strong academic background, such as in computer science or engineering.
• 3 to 5+ years of relevant experience.
• Preferred: experience with PostgreSQL, SQL, Python, REST/Graph APIs, Kafka, batch and file processing, Azure, Databricks/PySpark, Git and CI/CD, and knowledge graph or graph databases.
• Preferred: experience in data management, data governance, data cataloging or metadata platforms is a plus.
• Preferred: hands-on familiarity or integration experience with data management, governance, metadata or catalog platforms such as DataHub, OpenMetadata, Collibra or comparable tools.
• Preferred: practical knowledge of lineage and provenance, including OpenLineage, W3C PROV-oriented models and automated lineage capture.
• Preferred: practical experience or exposure to Elasticsearch or OpenSearch, and to Kafka or comparable message queues.
• Preferred: understanding of security and compliance engineering, including RBAC, ABAC, SSO/MFA, secrets management, audit logging, access governance, network controls and secure configuration baselines.
• Preferred: exposure to pandas for data analysis, profiling, transformation or automation is a plus.
• Preferred: familiarity with responsible use of coding copilots or AI-assisted developer workflows.

Conditions

Location: Toronto, Ontario, Canada.

Scheduled hours: 5.

Line of business: Technology Solutions.

Base pay range: $81,600 to $115,200 CAD.

Pay within the range depends on skills, experience, job knowledge, geographic location and business needs. Colleagues can progress through the range over time as they grow in the role.

You are welcome to ask about compensation and discuss it openly with your recruiter.

This role is subject to provincial employment regulations, which may vary across Canadian provinces and territories.

The company is committed to fair and equitable treatment of all colleagues.

Benefits

• Total rewards include base salary, variable compensation, health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs.
• Regular career, development and performance conversations with your manager.
• Access to an online learning platform and a range of mentoring programs.