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 that combines production coding and technical contribution with people leadership and delivery accountability. You will provide technical direction within the team’s domain, manage execution and operational risk, and partner with 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 is useful in guiding solutions, while the role remains accountable for team-level engineering excellence, delivery, and production outcomes. You will contribute across the full-stack codebase, including ReactJS and Java, and guide cloud-native applications, APIs, distributed services, event-driven integrations, data-processing workloads, and reusable platform capabilities. You will manage production health, significant incident response, durable remediation, service-level objectives, and communication of service health and risks to stakeholders. The position also includes building an inclusive, accountable team and strengthening engineering practices across teams. The role is based in Dallas, Texas. Scotiabank describes its benefit programs as flexible and designed to support employees’ 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, including the 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 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 product or platform scope.
Strong delivery and operational management capability, 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.
Remain hands-on in the ReactJS and Java codebase by implementing production solutions, developing prototypes and reference implementations, reviewing pull requests, improving tests and automation, and debugging complex 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 product, architecture, and engineering strategy.
Manage predictable team delivery and measurable outcomes, using engineering metrics to manage roadmap commitments, capacity, quality, risk, technical debt, dependencies, and improvement.
Drive engineering excellence through secure-by-design development, automated testing, CI/CD, infrastructure as code, observability, performance engineering, production readiness, incident management, and service-level objectives.
Guide the 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 and across teams by contributing to shared standards, reusable patterns, talent development, and communities of practice.