FP&A Data Analytics & AI Strategy, Sr. Manager (New York City)

About the role

The Senior Manager, Data Transformation will serve as the strategic and operational lead for the data, analytics, and reporting function supporting the FP&A organization. This is an individual contributor role responsible for the end-to-end data architecture, day-to-day reporting operations, and the long-term transformation roadmap that enables Finance to deliver faster, more accurate, and more insightful business partnership.

Responsibilities

• Data Strategy & Transformation Leadership
• Define and execute the multi-year data and reporting transformation roadmap for FP&A, aligned with broader Finance and enterprise data strategy.
• Lead the design and evolution of the FP&A data architecture, including data sources, integration layers, financial data models, and the semantic / reporting layer.
• Partner with IT, Data Engineering, and Enterprise Data teams to ensure FP&A requirements are represented in enterprise data platforms (e.g., data warehouse, lakehouse, master data, ERP).
• Champion a shift from manual, spreadsheet-driven processes toward automated, governed, and scalable reporting and planning solutions.
• Build the business case for transformation initiatives, including ROI, resource needs, and change management considerations.
• Day-to-Day Data & Reporting Operations
• Own end-to-end delivery of recurring FP&A reporting cycles, including monthly close reporting, management reporting packages, board materials, and ad hoc executive requests.
• Ensure the accuracy, timeliness, completeness, and consistency of all financial data and reports consumed by FP&A and business stakeholders.
• Establish and maintain SLAs, controls, and reconciliation processes between source systems (e.g., ERP, CRM, HRIS) and the FP&A reporting environment.
• Serve as the escalation point for data issues, reporting discrepancies, and stakeholder requests, driving root-cause analysis and durable fixes.
• Maintain documentation, data dictionaries, and lineage for key FP&A datasets, metrics, and KPIs.
• Serve as the business owner and administrator of the FP&A forecasting / planning tool, including model maintenance, hierarchy and metadata updates, user access, integrations, and ongoing enhancements to support planning and forecasting cycles.
• Process Transformation & Automation
• Identify and prioritize opportunities to streamline, standardize, and automate FP&A processes across planning, forecasting, reporting, and analytics.
• Lead the design and implementation of automated data pipelines, ETL/ELT workflows, and reporting solutions that replace manual Excel-based processes.
• Deploy modern BI and visualization tooling (e.g., Power BI, Tableau, Looker) to deliver self-service analytics for finance and business partners.
• Evaluate and implement EPM / planning platforms (e.g., Anaplan, Pigment, Workday Adaptive, OneStream) and integrations as part of the transformation roadmap.
• Apply continuous improvement and agile delivery practices to drive measurable cycle-time, accuracy, and productivity gains.
• Data Architecture & Governance
• Lead the design and ongoing stewardship of the FP&A data architecture, including financial data marts, dimensional models, hierarchies, and master data (e.g., chart of accounts, cost centers, legal entities, products).
• Establish data governance, quality, and controls frameworks specific to FP&A, in partnership with enterprise data governance functions.
• Define standards for metric definitions, source-of-truth datasets, and certified reports to drive consistency across the organization.
• Ensure FP&A data solutions adhere to security, privacy, SOX, and audit requirements.
• Stakeholder Partnership & Influence
• Act as a trusted advisor to FP&A leadership and business partners, translating business questions into data and reporting solutions.
• Proactively identify gaps, risks, and opportunities in the data and reporting environment — surface them, recommend solutions, and drive them to resolution without waiting to be asked.
• Partner cross-functionally with IT, Data Engineering, and external vendors to deliver on transformation initiatives, including requirements definition, solution design, and implementation oversight.
• Drive change management and enablement, including training, documentation, and adoption tracking for new tools and processes.
• Influence outcomes through expertise and collaboration rather than direct people management.

Qualifications

• Bachelor's degree in a relevant field (minimum requirement; advanced degrees are not required).
• 8+ years of progressive, hands-on experience that combines a strong understanding of financials with a data transformation background, including business intelligence, data analysis, and process transformation experience.
• Solid understanding of financial concepts and FP&A processes (budgeting, forecasting, long-range planning, management reporting, and variance analysis) — enough to partner credibly with finance stakeholders and translate their needs into data solutions.
• Strong data analysis skills — ability to independently explore, validate, and interpret large financial datasets, surface trends and anomalies, and turn raw data into clear, decision-ready insights.
• Proven track record delivering business intelligence solutions and modernizing reporting environments (e.g., Power BI, Tableau, Looker), including advanced Excel.
• Process transformation experience — identifying inefficiencies, redesigning workflows, and implementing automation to drive measurable improvements in cycle time, accuracy, and scalability.
• Hands-on expertise with modern data platforms and tools such as SQL, data warehouses (e.g., Snowflake, BigQuery, Redshift, Databricks), and ETL/ELT tools (e.g., dbt, Fivetran, Airflow).
• Hands-on experience owning or administering an EPM / forecasting / planning tool (e.g., Anaplan, Pigment, Workday Adaptive, OneStream, Hyperion), including model design, integrations, and end-user support.
• Working knowledge of ERP systems (e.g., Oracle, SAP, NetSuite, Workday).
• Track record of partnering with IT and Data Engineering on data architecture, integration, and governance.
• Excellent communication skills, with the ability to translate complex data concepts for finance and executive audiences.

Preferred Qualifications

• Experience in a public company or scaling high-growth environment with SOX compliance requirements.
• Familiarity with Python or other scripting languages for data manipulation and automation.
• Experience with AI / ML use cases in Finance (e.g., forecasting, anomaly detection, narrative generation).
• Prior experience in management consulting, Big 4 advisory, or a Finance Transformation Center of Excellence.

Key Competencies

• Proactive self-starter — anticipates needs, identifies issues and opportunities ahead of stakeholders, and drives them to resolution without waiting for direction.
• Strong analytical mindset — naturally curious about data, comfortable digging into details to validate accuracy and uncover insights.
• Strategic thinking with strong execution discipline — able to set vision and ship results.
• Bias for action and continuous improvement; comfortable navigating ambiguity.
• Strong systems thinking; sees data, process, and technology as one operating model.
• Influential communicator and collaborator across Finance, IT, and the business — able to drive outcomes through expertise and partnership rather than direct authority.
• Highly self-directed; thrives owning end-to-end work as an individual contributor.