AmeriLife · 2 months ago
VP of Enterprise Data Platform
Clearwater, FL
Full-time
Onsite
Mid, Senior Level, Lead/Staff
10+ years expAmeriLife is a leader in the development, marketing, and distribution of insurance solutions for retirement. They are seeking a strategic and technically adept Vice President of Enterprise Data Platform to lead the design, delivery, and operation of its enterprise data ecosystem, ensuring compliance and scalability while fostering a culture of innovation and continuous improvement.
Financial ServicesHealth CareHealth InsuranceInsuranceLife InsuranceMarketing
Responsibilities
Architect the Enterprise Data Platform: Define and maintain a reference architecture spanning ingestion, storage, compute, modeling, quality, observability, orchestration, and serving layers
Build Scalable Pipelines: Design and govern resilient pipelines from business applications into the enterprise data platform and downstream analytics services, ensuring schema drift tolerance and backward compatibility. Leverage Spark and PySpark for distributed processing, ETL optimization, and scalable ML workflows
Establish Enterprise Data Standards: Publish and maintain a governed enterprise data model and glossary, including SCD2 dimensions, point-in-time facts, conformed dimensions, lineage, SLAs, and usage policies
Implement SOX-Grade Controls: Deliver immutable logging, segregation of duties, maker-checker workflows, and reconciliation processes to ensure compliance and audit readiness. Expand compliance to include discovery and classification of PII and other sensitive data, encryption/masking, access controls, third-party risk, and audit-ready logging
Create 3rd Party Data Hub: Standardize intake patterns (SFTP, APIs, managed portal extracts) and enforce versioned data contracts per source for consistent 3rd party data onboarding
Partner Across Integration & Analytics: Collaborate with Application and Data Integration teams for API scalability, idempotent event processing, and batch patterns for large carrier files
Enable Secure Access & Hierarchies: Deliver a Hierarchy Service and enforce role-based and attribute-based access across systems and data domains
Power Advanced Analytics & AI: Operationalize workflows and model-serving capabilities to enable anomaly detection, enrichment, and mapping to accelerate AI adoption. Partner directly with Applied AI Engineering to design and operationalize the enterprise feature store for ML feature reuse and governance
Partner on Data Governance: Work closely with the Head of Data Governance to implement data quality frameworks and ensure metadata completeness across domains
Mentoring and Upskilling: Build a learning culture by coaching engineers on Spark and PySpark, cloud-native data engineering, observability, security, and cost-aware design. Provide technical reviews, pairing, and certification pathways to elevate team capabilities
Migrate from On-prem: Execute a phased migration from on-prem ETL to cloud-native pipelines, retiring technical debt while maintaining business continuity and SLAs. Sequence workloads by criticality, implement dual-run cutovers, and decommission legacy systems with clean lineage and documentation
Cost Optimization and Performance Management: Implement FinOps practices for cost baselining, right-sizing, autoscaling, and job-level cost allocation. Govern workloads with cluster policies, quotas, and prioritization. Optimize Spark and PySpark jobs for performance and cost efficiency
Qualification
Required
10+ years leading data engineering and architecture for complex, multi-system enterprises
Hands-on expertise with Spark and PySpark for distributed compute, ETL optimization, and scalable ML data pipelines
Experience with modern data platforms such as Databricks or Microsoft Fabric for efficient pipelines and analytics enablement
Proven success delivering governed data platforms and semantic layers at scale
Deep expertise in dimensional modeling (SCD2, point-in-time facts, conformed dimensions)
Experience with data quality frameworks, observability tooling, schema registry, and data contracts
Strong background implementing SOX-grade controls and sensitive-data protection standards (PII discovery, classification, encryption/masking, access controls, audit logging)
Demonstrated leadership managing multi-disciplinary engineering teams and vendor partners
Preferred
Experience in insurance distribution or financial services, including producer hierarchies, commissions, and carrier data integration
Familiarity with API integration platforms such as MuleSoft
Exposure to AI/ML enablement within enterprise data platforms, including feature store design and operationalization
Experience with FinOps practices and workload governance at scale
Company
AmeriLife
AmeriLife provide insurance and retirement solutions to enhance the lives of pre-retirees and retirees.
1001-5000 employees
H1B Sponsorship
AmeriLife has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (2)
Funding
Current Stage
Late StageTotal Funding
$395MKey Investors
Genstar Capital
2022-06-13Secondary Market
2020-01-07Acquired
2019-06-18Debt Financing· $395M
Leadership Team
Scott Perry
CEO
Tim Calvert
Chief Operating Officer
Recent News
2025-12-02
Company data provided by crunchbase