Senior Manager, Data Engineering

Scotiabank; Toronto; Vor Ort; CAD 100.000 - 140.000; Vollzeit

Zusammenfassung

Scotiabank is seeking a Senior Manager, Financial Data & Modeling Solutions Engineering in Toronto, Ontario. This role is crucial for designing and scaling enterprise-grade data and modeling solutions, significantly impacting financial planning, analytics, and regulatory reporting.

Ideal candidates will possess at least 7–10 years of experience in data engineering within the financial sector, alongside strong expertise in data modeling and cloud data platforms. The position offers the opportunity to lead cross-functional teams and enhance data governance and automation.

Qualifikationen

• 7–10+ years of experience in data engineering or platform engineering roles.
• Proven track record delivering enterprise-scale data and modeling solutions.
• Experience in financial services or regulated industries is strongly preferred.

Aufgaben

• Lead the design and delivery of end-to-end data and modeling solutions for Finance use cases.
• Partner with data engineering teams to develop robust data pipelines and governance mechanisms.
• Drive development of automated Finance solutions, including forecasting automation pipelines.

Kenntnisse

Data engineering

Data modeling

Cloud data ecosystems

Financial analysis

Stakeholder management

Executive communication

Tools

SQL

Power BI

Anaplan

Jobbeschreibung

Requisition ID: 263318

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

Scotiabank continues to be an industry leader for Financial Technology and Innovation. We have a history of safely leveraging new tools to enable new experiences for our customers, focusing on ensuring we protect their interests and goals. The results of this lead to modernization programs which aim to offer enriched information and transparencies to support the rapidly evolving payments community.

Role Overview

The Senior Manager, Financial Data & Modeling Solutions Engineering is a technology leadership role responsible for designing, building, and scaling enterprise‑grade data and modeling solutions that power Finance capabilities. Sitting within the Technology organization, this role enables financial planning, forecasting, regulatory reporting, and advanced analytics through modern data platforms, engineered modeling solutions, and integrated systems.

The role bridges financial domain expertise with engineering execution, ensuring Finance is supported by high‑quality, production‑grade data pipelines, reusable modeling frameworks, and scalable analytics solutions aligned with enterprise architecture and data strategy.

Key Responsibilities

• 1. Financial Data & Modeling Solutions Engineering
  • Lead the design and delivery of end‑to‑end data and modeling solutions for Finance use cases
  • Build and operationalize:
    • Driver‑based forecasting solutions
    • Scenario and simulation engines
    • Financial data products and reusable modeling components
  • Ensure solutions are scalable, performant, and production‑ready
• 2. Data Engineering & Platform Enablement
  • Partner with data engineering teams to develop:
    • Robust data pipelines and transformation frameworks
    • Curated Finance data domains and data products
    • High‑quality, governed datasets for modeling and analytics
  • Leverage modern cloud data platforms, warehouses, and lakehouse architectures
• 3. Modeling Platform Integration
  • Enable integration across:
    • ERP / GL systems
    • Risk and regulatory platforms
    • Planning tools (e.g., Anaplan or equivalent)
    • Enterprise data platforms
  • Design and implement semantic layers and data models that support finance use cases
• 4. Advanced Analytics & Automation
  • Drive development of automated and intelligent Finance solutions, including:
    • Forecast automation pipelines
    • Variance analysis and anomaly detection
    • Integration with AI/ML models (in collaboration with data science teams)
  • Embed analytics into end‑to‑end Finance workflows
• 5. Architecture Alignment & Standards
  • Ensure all solutions align with:
    • Enterprise architecture principles
    • Data governance, lineage, and quality standards
    • Security, audit, and compliance requirements
  • Contribute to defining target‑state architecture for Finance data and modeling
• 6. Governance, Risk & Regulatory Enablement
  • Embed controls for:
    • Data lineage and traceability
    • Model governance and validation
    • Auditability and regulatory compliance (e.g., BCBS 239)
  • Partner with Risk, Compliance, and Audit teams to ensure control effectiveness
• 7. Delivery & Engineering Leadership
  • Lead delivery of complex data and modeling engineering initiatives
  • Manage cross‑functional teams across:
    • Data engineering
    • Architecture
    • Finance stakeholders
    • Vendors (if applicable)
  • Drive Agile delivery practices and ensure high‑quality execution
• 8. Stakeholder Engagement & Translation
  • Act as a key interface between Finance and Technology
  • Translate business requirements into technically robust solutions
  • Communicate complex technical concepts in business‑relevant terms to senior stakeholders

Qualifications & Experience

Experience

• 7–10+ years of experience in:
  • Data engineering, analytics engineering, or platform engineering roles
  • Financial systems, reporting, or analytics environments
• Proven track record delivering enterprise‑scale data and modeling solutions
• Experience in financial services or regulated industries strongly preferred

Technical Skills

• Strong expertise in:
  • Data engineering (pipelines, ETL/ELT, transformations)
  • Data modeling (dimensional, semantic, analytical models)
  • Cloud data ecosystems (warehouses, lakehouses)
• Experience with:
  • SQL and data transformation tools
  • APIs and system integration patterns
  • BI and visualization tools (Power BI, Cognos, etc.)
  • Planning platforms (e.g., Anaplan – preferred)

Finance Domain Knowledge

• Good understanding of:
  • Financial planning & analysis (FP&A) processes
  • Financial and/or regulatory reporting
  • Key financial metrics, drivers, and hierarchies
• Ability to map Finance concepts into data and engineering abstractions

Leadership & Delivery Skills

• Strong engineering leadership and program delivery experience
• Ability to operate across business and technical domains
• Excellent stakeholder management and executive communication skills
• Experience working in large, matrixed organizations

Key Success Measures

• Delivery of scalable, high‑quality financial data and modeling solutions
• Improved data availability, usability, and performance for Finance
• Reduction in manual processing through automation and engineering
• Increased adoption of modern data and modeling platforms
• Strong compliance with architecture, governance, and regulatory standards

Why Join our Team

• Play a critical role in shaping data as a strategic asset across Finance and Risk
• Directly impact regulatory confidence, audit outcomes, and enterprise decision‑making
• Oversee the integration of data governance and AI‑driven innovation
• Partner with senior leadership on high‑visibility transformation initiatives

Location

Canada: Ontario: Toronto

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.