Finance Data Platform Leader with Databricks Lakehouse

Amerilife Group, LLC; Town of Florida (NY); Hybrid; USD 128,000 - 173,000; Full time

Benefits offered by this job

PTO

Medical, dental, vision insurance

Retirement savings plan

Disability insurance

Life insurance

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. This role reports to the Vice President of Enterprise Data & AI Platforms and will drive the Finance Data Platform and related financial data capabilities across Finance, Accounting, FP&A, Commissions, and other financial processes.

The candidate will manage a team of engineers and finance data specialists, translating complex

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 workloads.
• Strong hands-on experience with Databricks, 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 as Azure or AWS.
• Strong understanding of financial data and processes, including P&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.

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.
• 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.
• 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.
• 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.
• 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.
• 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.

Skills

Leadership

Stakeholder management

Finance data domain

Data engineering

Cloud platforms (Azure/AWS)

Tools

Databricks

Apache Spark

Delta Lake

SQL

Job description

AmeriLife is seeking a Senior Manager, Finance Data Platform to lead the engineering, delivery, operations, and modernization of our enterprise finance data ecosystem. This role reports to the Vice President of Enterprise Data & AI Platforms and will drive the Finance Data Platform and related financial data capabilities across Finance, Accounting, FP&A, Commissions, and other financial processes.

The candidate will manage a team of engineers and finance data specialists, translating complex