Engineering Manager, Data Policy

Scotiabank•Dallas, TX

About The Position

As an Engineering Manager on Scotiabank’s Data & AI Technology team, you will lead an engineering team responsible for designing, building, and operating secure, resilient, and scalable enterprise platforms and products within a defined product or platform capability. This is a hands-on engineering leadership role: you will write and review production code, prototype solutions, troubleshoot complex issues, and contribute directly to critical technical outcomes while managing and developing the team. You will provide technical direction within the team’s domain, manage execution and operational risk, and partner across product, architecture, cybersecurity, infrastructure, and business teams. Experience with data platforms and data management disciplines such as metadata inventory, lineage, quality, governance, and secure data use can help guide solutions in this domain. The role is accountable for team-level engineering excellence, delivery, and production outcomes. The position combines technical contribution with people leadership and delivery accountability. The manager leads team development and execution, guides engineering decisions within the team’s scope, and manages service health and operational risk. The role also contributes to engineering practices and shared standards across adjacent teams. The job is based in Dallas, Texas, United States. Scotiabank describes itself as an inclusive and accessible employer and offers flexible benefit programs focused on family, financial, physical, mental, and social health needs.

Requirements

Bachelor’s or master’s degree in computer science, engineering, or a related field, or equivalent practical experience.
Strong experience leading an engineering team delivering and operating enterprise-scale, production-grade software, platforms, or distributed systems in a complex and regulated environment.
Demonstrated success managing engineers, including talent assessment, coaching, performance management, workforce planning, succession, and organizational design.
Strong, current coding proficiency and technical depth, with demonstrated ability to design, build, test, review, and troubleshoot production-grade solutions.
Experience with cloud architecture, APIs and microservices, distributed and event-driven systems, security, resiliency, automated testing, and scalable integration patterns.
Experience with cloud platforms such as Azure or GCP, containerized workloads, CI/CD, infrastructure as code, observability, reliability engineering, production support, and cost-conscious platform operations.
Ability to translate established product and engineering strategy into team-level technical direction, evaluate architecture and build-versus-buy trade-offs, manage technical debt, and lead modernization within a defined scope.
Strong delivery and operational management skills, including roadmap execution, capacity and dependency management, risk controls, engineering metrics, incident leadership, and continuous improvement.
Ability to influence technology, product, and business stakeholders, communicate complex decisions clearly, and build alignment across adjacent teams without relying solely on direct authority.

Nice To Haves

Experience with data platforms and exposure to data management disciplines such as metadata inventory, lineage, quality, governance, and secure data use.

Responsibilities

Lead, grow, and retain a high-performing engineering team; set expectations, coach performance, support succession and development planning, and foster an inclusive culture of accountability, customer focus, and continuous improvement.
Contribute hands-on to the ReactJS and Java codebase by designing and implementing production solutions, prototyping, reviewing pull requests, improving tests and automation, and debugging application and platform issues.
Provide technical direction within the team’s domain, lead critical design decisions, manage dependencies with adjacent teams, and resolve engineering trade-offs in alignment with established strategy.
Manage predictable team delivery and measurable outcomes using engineering metrics to oversee roadmap commitments, capacity, quality, risk, technical debt, dependencies, and continuous improvement.
Drive engineering excellence across the software lifecycle, including secure-by-design development, automated testing, CI/CD, infrastructure as code, observability, performance engineering, production readiness, incident management, and service-level objectives.
Guide design and operation of cloud-native applications, APIs, distributed services, event-driven integrations, data-processing workloads, and reusable platform capabilities within the team’s scope.
Manage production health and operational risk; lead responses to significant incidents, ensure durable remediation, and communicate service health, risks, decisions, and resource needs to stakeholders.
Strengthen engineering practices within the team and across adjacent teams through shared standards, reusable patterns, talent development, and communities of practice.