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 partnerships.
Responsibilities
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-based processes toward automated, governed, and scalable reporting and planning solutions.
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.
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.
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.
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.
Demonstrated experience leading data transformation, finance modernization, or reporting automation initiatives end-to-end as an individual contributor.
Strong 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.