AVP Cloud Data Analytics Architecture

Responsibilities

• Lead the cloud data architecture team and help scale the Data and Analytics organization for various finance groups.
• Work with the business to gather data and analytical requirements; design, develop and deploy Enterprise Cloud Data solutions.
• Integrate data from disparate sources to load to the cloud, hybrid and multi-cloud.
• Design, develop and monitor processes to transfer data between cloud systems and/or external vendors.
• Collaborate with technical leaders to define api-first, web services, event based processes to maintain accuracy, lineage, metadata, integrity and efficiency of data across multiple levels of curation and consumption.
• Provide data modeling standards, frameworks and templates to support the business.
• Organize, catalog and define enterprise data to support AI, Machine Learning, Data Science and Reporting.
• Ensure the cloud, data, Machine Learning and AI platform is scalable and secure to meet future growth and requirements of business domains.
• Lead the strategy, development, and delivery of Finance data assets within the Finance Center of Excellence (COE), while managing a team of data engineers responsible for data engineering, analysis and reporting.
• Drive the data engineering roadmap, implement process improvements, and deliver scalable SQL-based reporting and data solutions.
• Architect the data and analytics platform to support Company's vision, goals and strategies.
• Partner with the Finance business teams to design and implement governed, finance-critical data products—ensuring accuracy, stewardship alignment, and seamless integration with enterprise data engineering standards.
• Enable various Finance initiatives by engineering scalable, reliable datasets that support Securitization, FP&A reporting, Oracle Fusion-based workflows, Gen-AI Finance Assistant use cases, and advanced analytics across Finance.
• Translate broad strategies into specific data architecture plans, utilizing existing resources and information to achieve strategic objectives and improve business results.
• Collaborate with Data Leadership to define cloud data architecture, business, Digital Transformation and Data & Analytics priorities and goals.
• Collaborate with VP Cloud Data Analytics Architecture on department's performance to ensure accountability for achieving business results.
• Architect the flow of data from transactional systems, data management and master data layer, to the cloud data and analytics platform and consuming applications.
• Collaborate with various VP across finance groups to define and report the needs of product/architecture releases with respect to business objectives, security, data dependency, compliance, and timeliness of releases.
• Architect and develop consistent metrics to measure data quality, security, utilization and consumption for management and audit.
• Collaborate with business and technical teams to develop end-to-end Enterprise solutions for data, analytics, machine learning, artificial intelligence in the cloud.
• Coach, mentor, and train data engineering team members to establish a consistent level of quality, accuracy, accountability and compliance with department standards.
• Aid leadership in determining the annual business plan and setting the budgetary requirements for the department and manage each plan to ensure compliance and completion.
• Champion an environment that promotes trust, continuous improvement, innovation, quality outcomes and self-development.
• Develop relationships with key customer business and technical decision makers: drive long-term cloud data adoption within the company; enable cloud data advocacy.
• Share insights and best practices, and connect with teams to remove key blockers.

Qualifications

• Advanced knowledge of cloud data architecture to support modeling, reporting, machine learning, artificial intelligence and analytics.
• Advanced knowledge of cloud and data security methodologies, policies, standards and best practices.
• Advanced knowledge of best practices in cloud data governance, architecture and tools for regulatory landscape for financial institutions.
• Advanced knowledge of cloud data architecture, data operations, data engineering, full-stack (dev ops, data dev ops, and dev sec ops).
• In-depth knowledge of cloud data security frameworks.
• Wide-ranging understanding of general information technology standards and the Company’s systems, such as Provenir, CPW, General Ledger, Oracle ERP, etc.
• Advanced knowledge of Azure Data Architecture - Azure Data factory, Azure Data Lake, Microsoft Synapse, Databricks and PySpark utilizing structured and unstructured data.
• Advanced knowledge of developing data engineering solutions in Python.
• Advanced knowledge of creating cloud MDM, CDC, Data Lineage, Metadata Management solutions.
• Advanced knowledge of utilizing SQL to transform, transport, copy and export data in the cloud.
• Advanced knowledge of developing and optimizing data pipelines from source to target systems.
• Advanced knowledge of transforming and curating multiple data types in Databricks.
• Advanced knowledge of event driven data architecture in the cloud.
• Advanced knowledge of utilizing APIs and web services in the cloud (integrate systems, platforms and data sources).
• Experience developing data solutions in the cloud for Marketing, Customer Experience, Data Science, Finance and Treasury.
• Experience developing cloud data domains, such as customer360.
• In-depth knowledge of industry-standard enterprise data management and integration technologies and methodologies, such as Informatica.
• In-depth knowledge of Agile SAFe methodologies and the software development life cycle.
• Advanced working knowledge of information systems and operations.
• Experience working with transactional, temporal, time series, structured and unstructured data in the cloud.
• Experience with large-scale enterprise-wide migration of workloads to the cloud.
• Effective written and verbal presentation skills with an ability to communicate complex technology, architecture, tools, processes and solutions with senior management.
• Ability to interact collaboratively with internal customers and external vendors on highly complex enterprise cloud data and platform strategies.
• Demonstrated ability to effectively lead, motivate, challenge, organize and supervise a team of data architects and full stack engineers.
• Demonstrated quantitative skills and ability to apply complex cloud data architecture principles.
• Demonstrated expertise in leading distributed teams of engineers and architects to align on key architectural and technical decisions and direction – and guiding those through successful execution.
• Proven cloud knowledge and deep understanding of Azure services – Azure Data Factory, Service Bus, ADLS2, Delta Lake, Cosmos DB, Synapse.
• Experience with traditional RDBMS (Oracle, Teradata, DB2).
• Experience with SAS, R, Ruby, Java and C.
• Experience with Open-Source Tools in an Azure, AWS and/or Google Cloud.
• Experience with Azure Data, Data Design and Curation required to support Advanced Analytics (Machine Learning, Risk, Artificial Intelligence).
• Experience with traditional RDBMS (Oracle, Teradata, DB2).
• Experience with large-scale enterprise-wide migration of workloads to the cloud.
• Experience with software development practices like DevOps and CI/CD tool chains, Azure DevOps, GitHub.
• Experience with management or leadership roles.

Pay

Competitive pay and bonus eligibility.

Schedule

Flexible hybrid work environment, 3 days a week in the office.