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 enterpriseDatabricks Lakehouseplatform.
- 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 members92 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 operatinglarge-scale enterprise data platformssupporting business-critical workloads.
- Strong hands-on experience withDatabricks, Apache Spark, Delta Lake, or comparable modern cloud data technologies.
- Advanced SQL skills with strong knowledge of data engineering, ETL/ELT, integration, pipeline design, and performance optimization.
- Strong experience with cloud platforms such asAzure or AWS.
- Strong understanding of financial data and processes, including multiple areas such asP&L, FP&A, General Ledger, commissions, banking, journal entries, financial reporting, reconciliation, allocations, attribution, planning, and forecasting.
- Experience supporting data environments where accuracy, auditability, lineage, reconciliation, and financial controls are critical.
- Strong knowledge of enterprise data modeling, dimensional modeling, and modern lakehouse architectures.
- Experience managing production data workloads and resolving complex data, pipeline, reconciliation, and platform issues.
- Experience implementing automated testing, monitoring, data quality, CI/CD, and production controls.
- Demonstrated ability to translate complex Finance requirements into scalable data solutions.
- Proven ability to lead teams operating across strategic initiatives, rapid enhancements, and business-critical production responsibilities.
- Strong communication and stakeholder-management skills with the ability to partner effectively with Finance and senior technology leaders.
Preferred Qualifications
- Experience building, leading, or modernizing aFinance Data Platform, Finance Data Mart, Finance Data Warehouse, or comparable financial data ecosystem.
- Experience migrating legacySQL Server, SSIS, ADF, stored procedure, or traditional data warehouseworkloads to Databricks or another cloud-native platform.
- Experience with commission and incentive compensation platforms such asVaricentor comparable technologies.
- Experience with financial planning, consolidation, and performance management platforms such asOneStreamor similar solutions.
- Experience within insurance, financial services, distribution, commissions, or other transaction-intensive industries.
- Experience working with master and reference data involving companies, legal entities, carriers, products, producers, policies, contracts, accounts, and organizational hierarchies.
- Familiarity withData Vault 2.0, dimensional modeling, medallion architecture, Unity Catalog, data lineage, and modern data governance practices.
- Experience managing blended teams consisting of employees, contractors, and strategic delivery partners.
- Databricks certification and/or relevant Azure or AWS certifications preferred.
Leadership Profile
The ideal candidate combines the mindset of aFinance data leader, hands-on data engineer, and platform operator. This individual should be equally comfortable discussing a P&L or commission reconciliation with Finance, reviewing SQL and pipeline logic with an engineer, diagnosing a production data issue, challenging a data model, and defining the roadmap for modernizing FDM capabilities on Databricks. Success in this role requires strong technical judgment, financial data fluency, operational discipline, and the ability to bring structure to a fast-moving environment without introducing unnecessary bureaucracy. The Senior Manager will be expected to make the Finance Data Platform increasingly scalable, automated, governed, and reliable while preserving the responsiveness Finance requires from a mission-critical data function.
Compensation
- Salary: $150,000
- This role may be eligible for a discretionary annual bonus.
- Salary offers will varycommensuratewith experience, education, skills, and training
What AmeriLife Offers
A comprehensive benefits package that includes PTO, medical, dental, vision, retirement savings, disability insurance, and life insurance.
