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Salary: USD 200,000 - 250,000 / annual
iCapital is seeking a Data Engineering Senior Vice President to lead the evolution of the enterprise data platform that powers AI, automation, analytics, and data-driven decision-making across the firm. This role is responsible for defining and executing the architectural vision, roadmap, and operating model for a modern, AI-ready data ecosystem built on cloud technologies and established engineering capabilities.
Key responsibilities include:
- Define and own iCapital's enterprise data architecture, including the Snowflake platform, semantic layer, reusable data products, and AI-ready ecosystem
- Establish standards for data engineering, governance, security, observability, quality, and documentation
- Own platform reliability, SLAs, DataOps practices, and incident management
- Lead architectural strategy, tooling decisions, and platform investment recommendations
- Develop and execute the multi-year Data Engineering roadmap aligned to business and AI priorities
- Translate enterprise data strategy into prioritized engineering initiatives and platform capabilities
- Build business cases for platform investments and proactively address technical debt and scalability needs
- Partner with business and technology leaders to deliver data products supporting enterprise objectives
- Communicate platform progress, risks, and investment decisions to executive stakeholders
- Build and lead a high-performing Data Engineering organization and culture
The role works in-office Monday–Thursday with remote flexibility on Friday. Compensation includes equity for all full-time employees and an annual performance bonus, plus comprehensive benefits including employer-matched retirement, subsidized healthcare (100% employer-paid dental and vision), telemedicine, virtual mental health counseling, parental leave, and unlimited PTO.
REQUIREMENTS:
- 12+ years of experience in data engineering, including 5+ years leading large-scale engineering organizations across multiple functions
- Proven track record designing, building, and operating enterprise-scale cloud data platforms (Snowflake, Databricks, or equivalent), including architecture, security, governance, and cost optimization
- Deep expertise establishing data engineering best practices across pipeline design, data quality, observability, data contracts, documentation, and operational support
- Demonstrated success developing multi-year platform strategies, securing investment, prioritizing initiatives, and delivering measurable business outcomes
- Experience partnering with and presenting to executive stakeholders within regulated industries, translating complex technical concepts into business impact
- Hands-on experience with analytics engineering, semantic layer development, and modern data transformation frameworks such as dbt
- Financial services experience within asset management, wealth management, fintech, banking, or insurance, including knowledge of regulated data environments and governance requirements
- Deep expertise in Snowflake architecture, performance optimization, security, and data sharing at enterprise scale
- Knowledge of alternative investments, wealth management, fund administration, or related financial services domains
- Experience building AI- and ML-enabled data platforms, including semantic layers, feature stores, model-serving infrastructure, or LLM-integrated architectures
- Experience with Informatica or comparable enterprise data catalog, metadata management, and MDM platforms
- Proven success scaling data engineering organizations through periods of rapid growth, including organizational design, hiring, and leadership development
