Senior Manager, Finance Data Platform

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For over 50 years, AmeriLife has been a leader in the development, marketing and distribution of annuity, life and health insurance solutions for those planning for and living in retirement.

Associates get satisfaction from knowing they provide agents, marketers and carrier partners the support needed to succeed in a rapidly evolving industry.

Job Summary

AmeriLife is seeking a Senior Manager, Finance Data Platform to lead the engineering, delivery, operations, and modernization of our enterprise finance data ecosystem.

Reporting directly to the Vice President of Enterprise Data & AI Platforms, this leader will have responsibility for the Finance Data Platform (FDM) and the broader data capabilities supporting Finance, Accounting, FP&A, Commissions, Banking, General Ledger, financial reporting, attribution, reconciliation, and related financial processes.

This is a hands-on technology leadership role requiring a strong combination of enterprise data platform experience, financial data domain knowledge, engineering depth, and people leadership. The Senior Manager will lead a team of engineers and finance data specialists while working closely with Finance stakeholders to translate complex financial requirements into reliable, scalable, and well-governed data solutions.

A key mandate for this role will be evolving existing FDM capabilities into a modern, enterprise-grade Finance Data Platform built on Databricks, while maintaining the responsiveness required to support fast-moving Finance priorities and business-critical operations.

Job Description

Key Responsibilities

Finance Data Platform Leadership

• •Lead the engineering, delivery, operations, and ongoing evolution of the Finance Data Platform.
• •Provide day-to-day leadership for engineers, finance data specialists, and partner resources supporting FDM and related finance data capabilities.
• •Establish clear priorities across Finance enhancements, strategic initiatives, production issues, reconciliations, data quality, technical debt, and platform modernization.
• •Build an operating model that supports rapid Finance-driven changes while maintaining engineering discipline, reliability, governance, and appropriate controls.
• •Partner closely with Finance, Accounting, FP&A, Commissions, Data Architecture, Data Engineering, and enterprise technology teams.
• •Translate complex Finance requirements and business rules into scalable technical solutions and executable engineering priorities.
• •Establish clear accountability across engineering, functional expertise, QA, delivery, and operational support.

Finance & FDM Domain

• •Develop deep expertise in the existing FDM ecosystem, including its business processes, data models, transformations, integrations, dependencies, and downstream consumers.
• •Lead data capabilities supporting:
• •General Ledger and journal entries
• •P&L and financial performance
• •FP&A, budgeting, planning, and forecasting
• •Commissions and compensation
• •Banking and cash transactions
• •Revenue and expense attribution
• •Carrier, producer, policy, contract, and product financial activity
• •Entity, company, product, and organizational attribution
• •Financial reconciliation and controls
• •Management and statutory financial reporting

• •Partner with Finance stakeholders to understand calculation logic, mappings, hierarchies, allocations, attribution rules, reconciliation requirements, and reporting dependencies.
• •Ensure financial data can be traced and reconciled from source systems through transformation and downstream consumption.
• •Support integrations with financial planning, commission, accounting, reporting, and enterprise performance management platforms.

Databricks & Enterprise Data Engineering

• •Lead the modernization and migration of Finance data capabilities onto the enterprise Databricks Lakehouse platform.
• •Design and oversee scalable ingestion, transformation, integration, and publishing patterns for complex financial datasets.
• •Apply modern lakehouse and medallion architecture principles across Bronze, Silver, and Gold layers.
• •Drive engineering standards including reusable frameworks, metadata-driven pipelines, automated testing, CI/CD, observability, and infrastructure automation.
• •Work across databases, APIs, files, SFTP feeds, enterprise applications, and other structured and semi-structured data sources.
• •Optimize Databricks workloads for performance, scalability, reliability, and cost.
• •Maintain strong SQL and data engineering standards across the team.
• •Partner with enterprise Data Architecture and Engineering leadership on data models, integration patterns, architecture standards, and platform strategy.
• •Drive the progressive retirement and simplification of legacy FDM components as capabilities transition to the enterprise data platform.

Financial Data Modeling, Quality & Controls

• •Ensure data models appropriately represent financial transactions, accounts, entities, products, carriers, producers, policies, contracts, commissions, and organizational hierarchies.
• •Establish strong reconciliation capabilities across source systems, FDM, Databricks, General Ledger, financial applications, and downstream reporting.
• •Ensure appropriate historical tracking, auditability, lineage, and point-in-time analysis for critical financial data.
• •Partner with Data Architecture and Governance teams to establish consistent business definitions, metadata, lineage, ownership, and data quality standards.
• •Establish automated controls for completeness, accuracy, timeliness, duplication, referential integrity, and financial reconciliation.
• •Ensure appropriate security and access controls for sensitive financial information.
• •Drive root-cause analysis and permanent remediation of recurring data quality and reconciliation issues.

Delivery & Operational Excellence

• •Lead execution across Finance data projects, enhancements, defects, operational requests, and production issues.
• •Establish a delivery model capable of supporting fast-paced Finance requirements that may not always align to traditional sprint-based development cycles.
• •Create clear processes for distinguishing and managing enhancements, strategic projects, production incidents, defects, and recurring operational activities.
• •Balance immediate Finance priorities with long-term platform modernization and technical sustainability.
• •Establish service expectations, prioritization mechanisms, escalation paths, and measurable delivery outcomes.
• •Reduce manual processing and operational dependencies through automation and engineering improvements.
• •Establish monitoring, alerting, incident management, and production-readiness practices for critical Finance data pipelines.
• •Coordinate internal teams and external delivery partners while maintaining clear internal accountability for outcomes.

People Leadership

• •Lead, mentor, and develop a high-performing Finance Data Platform team.
• •Build a team with the right combination of data engineering, financial domain, functional, and operational expertise.
• •Develop team members’ understanding of both the technology and the financial processes supported by the platform.
• •Create clear ownership and accountability while enabling engineers and specialists to operate with appropriate autonomy.
• •Manage internal employees, contractors, and strategic delivery partners.
• •Participate in hiring, workforce planning, performance management, and capability development as the Finance Data Platform organization evolves.

Required Qualifications

• •10+ years of experience across data engineering, enterprise data platforms, data architecture, financial data systems, or related disciplines.
• •3+ years of experience leading data engineering, data platform, or financial data teams.
• •Demonstrated experience designing, building, or operating large-scale enterprise data platforms supporting business-critical w