Manager, Data Engineering - Finance Data Foundations

• Leading the delivery of finance domain data migration projects with clear milestones, quality controls, and operational readiness
• Designing and maintaining reusable data ingestion and transformation frameworks aligned with enterprise engineering standards
• Ensuring data consistency, lineage, and trustworthiness across finance and enterprise data domains
• Collaborating with business and technical stakeholders to enable analytics, forecasting, and AI readiness for finance data
• Driving operational excellence across engineering practices, optimizing for cost, performance, and maintainability
• Design, develop, and maintain robust batch and streaming data pipelines across Azure Data Factory, Databricks, Informatica, and SQL environments, ensuring scalability, reliability, and operational efficiency
• Closely work with vendors, contractors and other FS teams to operationalize the data migration process for the hotels
• Implement and oversee CI/CD workflows, Infrastructure as Code (IaC), and automated testing frameworks (unit, integration, and data validation) with built-in monitoring and observability to meet defined SLAs and SLOs
• Operationalize data quality by integrating Informatica IDQ into finance workflows for profiling, rule-based validation, and continuous data quality monitoring
• Apply governance standards by embedding metadata, cataloging, and lineage practices in collaboration with the Data Strategy & Governance team
• Monitor and tune pipeline performance and Azure cost utilization
• identify opportunities for optimization across compute, storage, and workload scheduling
• Support the creation of certified datasets and semantic models to enable accurate and trusted Power BI self-service analytics for finance stakeholders
• Collaborate closely with Data Science and Analytics teams to deliver curated, model-ready data assets that comply with privacy and governance policies
• Lead end-to-end finance data migration projects, including data discovery, profiling, mapping (e.g., chart of accounts, subledgers), data conversion, validation, parallel runs, reconciliation, cutover execution, and hypercare support
• Document and enforce financial data controls, ensuring transparency, traceability, and compliance throughout migration and integration processes
• Apply established enterprise data architecture and engineering standards to ensure consistent, scalable, and governed design of finance data solutions across Azure, Databricks, and Informatica environments
• Collaborate closely with Enterprise Architecture and the Director of Data Engineering to align finance data engineering practices with enterprise technology strategy, security controls, and cloud infrastructure standards
• Design and implement finance data models and integration patterns that enable analytics, forecasting, and AI workloads while maintaining alignment with enterprise foundational frameworks
• Lead data modeling activities (conceptual, logical, and physical) for finance and related domains, ensuring traceability, accuracy, and conformance with the Unified Data Model
• Embed governance and data quality practices (profiling, rules, lineage, metadata management) into finance data engineering workflows using Informatica IDQ and Unity Catalog
• Support architectural design and technical delivery for enterprise programs such as Finance Transformation, Lakehouse modernization, and Commercial Analytics, ensuring all solutions adhere to architectural best practices
• Contribute to solution design reviews and technical documentation, ensuring performance, maintainability, and compliance with Four Seasons’ data engineering standards
• Partner with Data Governance and Business Stakeholders to ensure finance data solutions reinforce stewardship, cataloging, and certification practices for trusted reporting and analytics
• Stay informed on emerging technologies and architectural patterns (e.g., Lakehouse optimizations, data mesh, AI-driven engineering) and identify practical improvements to strengthen foundational capabilities
• Ensure compliance with enterprise architecture and governance processes for all finance-related data initiatives
• Coordinate cross-functional collaboration among data engineers, architects, analysts, and finance teams to maintain alignment with IT strategy and business objectives
• Translate architectural direction into executable tasks, guiding engineering teams in the development and implementation of finance data models, frameworks, and pipelines
• Support project planning and execution, including scoping, resourcing, and milestone tracking for finance data initiatives
• Conduct pre- and post-implementation validation to confirm alignment with business requirements, data standards, and performance benchmarks
• Collaborate with internal and external partners, including vendors and system integrators, to ensure high-quality delivery of finance data projects and adherence to contractual obligations
• Provide subject matter expertise in finance data engineering, assisting technical teams in resolving complex design or performance issues
• Proactively communicate project status, risks, and dependencies to leadership, escalating critical issues that may impact delivery timelines or quality
• Promote continuous improvement through feedback loops, retrospectives, and optimization of engineering practices to enhance quality, efficiency, and team collaboration

• Minimum 5-8 years experience Data Engineering
• with experience in Azure using Databricks
• Bachelor’s degree Required
• MBA or Master’s in Engineering preferred
• Expert in Data Engineering in Microsoft Azure Environment + Toolsets (ADF, Synapse, Data Bricks, Cosmos DB, FunctionApps, Logic Apps etc)
• Lakehouse experience using Databricks
• Azure platform administration
• Data Governance Software experience
• Microsoft Power BI delivery and support
• Strong SQL query skills
• Strong history in Python, Pyspark, or Scala
• Data process improvement
• Working in large data sets
• Confluence, Jira, TestRail
• Helpdesk Tools and methods
• Microsoft Visio
• Microsoft Office Suite, very strong Excel
• Excellent verbal and written communication skills
• Excellent organizational and time management skills
• High degree of self-motivation (strong initiative)
• Effective personal persuasion skills
• Be able to manage volume of work and deal with global conference calls
• Strong technical expertise in data engineering and data architecture within Azure and Databricks ecosystems
• Proven ability to deliver results through others, balancing hands-on work with leadership oversight
• Excellent team management and fostering a high-performance culture
• Solid leadership skills with experience driving data migration, integration, and transformation projects, especially in finance domains
• Strong financial and budgeting acumen, ensuring cost-effective delivery and platform optimization
• Excellent conceptual, analytical, and problem-solving abilities, with sound judgment and decision-making

MBA or Master’s in Engineering preferred