Data and AI Engineer

Scotiabank; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

Scotiabank is seeking an experienced Data and AI Engineer in Toronto to shape solution architecture across software, data, and AI/ML. You will own end-to-end designs, define roadmaps, and lead complex delivery from discovery to production using Databricks, Lakehouse, and GKE.

You will design governed AI, scalable data products, and secure cloud-native patterns, while mentoring engineers and coordinating with Architecture, Security, and business stakeholders in a highly regulated banking

Qualifications

• University degree in Computer Science, Software Engineering, Data Science or equivalent practical experience.
• 4+ years of progressive experience in software engineering, data engineering, AI/ML, or cloud-native delivery with production systems.
• Advanced Python and SQL skills with strong API development and testing practices.
• Hands-on experience with Databricks, Spark/PySpark, scalable processing, and Lakehouse/Medallion architecture.

Responsibilities

• Own end-to-end solution design, architecture trade-offs, non-functional requirements, and implementation patterns for complex AI, data, and software products.
• Provide technical expertise across engineers and workstreams; define roadmaps and resolve blockers and dependencies.
• Lead secure cloud-native application design on GKE with containerized services and APIs.
• Design governed Generative AI and agentic solutions using LLMs, RAG, embeddings, memory, and human-in-the-loop patterns.
• Architect scalable data products and pipelines using Databricks, Spark/PySpark, Delta/Lakehouse across Bronze, Silver, Gold layers.

Skills

Python

SQL

AI/ML

Data engineering

Software architecture

Cloud experience

Education

University degree in Computer Science/Software Engineering/Data Science

Tools

Databricks

Spark/PySpark

Lakehouse architecture

Medallion architecture

Kubernetes (GKE)

Kafka

Airflow

Vector/NoSQL databases

Job description

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Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

The Role:

The Data and AI Engineer provides hands on technical expertise across software engineering, data engineering, and AI/ML. This role shapes solution architecture, establishes engineering standards, and leads complex delivery from discovery through production using Databricks/Lakehouse, GKE, cloud-native services, and governed Generative AI patterns.

Is this role right for you? In this role you will:

Own end-to-end solution design, architecture trade-offs, non-functional requirements, and implementation patterns for complex AI, data, and software products.

Provide technical expertise across engineers and workstreams; define roadmaps, sequence delivery, and resolve high-impact blockers and dependencies.

Lead secure cloud-native application design on GKE, including containerized services, APIs, stateless patterns, autoscaling, resilience, and service integration.

Design governed Generative AI and agentic solutions using LLMs, RAG, embeddings/vector search, memory, orchestration, guardrails, policy controls, evaluation, and human-in-the-loop patterns.

Lead integration with enterprise AI gateways and model-access services; assess migration impacts and recommend options that minimize rework and operational risk.

Architect scalable data products and pipelines using Databricks, Spark/PySpark, Delta/Lakehouse, and Medallion patterns across Bronze, Silver, and Gold layers.

Establish standards for Python, SQL, APIs, testing, code review, CI/CD, observability, documentation, and reusable components.

Own production readiness, including performance, capacity, availability, security, vulnerability remediation, deployment controls, rollback, monitoring, and incident response.

Drive AI/ML governance through evaluation criteria, ground-truth datasets, response and override logging, traceability, auditability, and business validation.

Partner with Architecture, Data Platform, Security, AI Risk, and business stakeholders to secure alignment, communicate risk, and influence target-state decisions.

Mentor engineers through design reviews, code reviews, and technical coaching, reducing dependency on individual contributors and raising team capability.

Do you have the skills that will enable you to succeed in this role? We'd love to work with you if you have:

University degree in Computer Science, Software Engineering, Data Science, Engineering, or a related STEM discipline, or equivalent practical experience.

4+ years of progressive experience in software engineering, data engineering, AI/ML, or cloud-native delivery, including technical leadership on production systems.

Advanced Python and SQL skills with strong software design, API development, and testing practices.

Hands-on experience with Databricks, Spark/PySpark, scalable processing, and Lakehouse/Medallion architecture.

Experience designing and operating distributed cloud-native applications, APIs, and data platforms.

Experience leading design reviews, resolving complex technical issues, and mentoring engineers.

Ability to influence architecture, platform, security, risk, business, and delivery stakeholders.

Experience delivering governed AI solutions in banking or another highly regulated industry.

Experience with enterprise AI gateways, model hubs, MCP-based integrations, agent-to-agent patterns, Kafka, Airflow, or vector/NoSQL databases.

Experience preparing architecture artifacts and presenting at architecture, security, or risk governance forums.

What's in it for you?

Diversity, Equity, Inclusion & Allyship - We strive to create an inclusive culture where every employee is empowered to reach their fullest potential, respected for who they are, and are embraced through bias-free practices and inclusive values across Scotiabank. We embrace diversity and provide opportunities for all employee to learn, grow & participate through our various Employee Resource Groups (ERGs) that span across diverse gender identities, ethnicity, race, age, ability & veterans.

Accessibility and Workplace Accommodations - We value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. Scotiabank continues to locate, remove and prevent barriers so that we can build a diverse and inclusive environment while meeting accessibility requirements.

Upskilling through online courses, cross-functional development opportunities, and tuition assistance.

Competitive Rewards program including bonus, flexible vacation, personal, sick days and benefits will start on day one.

Dynamic Ecosystem - Free tea & coffee, universal washrooms, and lots of space for team collaboration.

Community Engagement - No matter where you choose to work from; we offer opportunities for community engagement & belonging with our various programs.

Location(s): Canada : Ontario : Toronto

Scotiabank is a leading bank in the Americas. Guided by our purpose: "for every future", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets. At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone.