Data Engineer - Vice President

iCapital • New York, NY

13h • $160,000 - $200,000 • Hybrid

About The Position

iCapital is seeking a strategic, product-oriented, and technical Data Engineer to help scale its Enterprise Analytics Platform and shape how data is accessed across the organization. The role leads the design and evolution of trusted, governed, and scalable data products that power analytics, reporting, operational workflows, and AI-driven capabilities. It is hands-on and highly collaborative, with direct influence on iCapital’s long-term data strategy, AI readiness, and enterprise data ecosystem.

The position works with business stakeholders, product managers, Engineering teams, Data Governance, domain owners, and Analytics teams to translate needs into data product strategies and platform capabilities. It designs semantic models and business context, builds and optimizes data pipelines and platform infrastructure, and advances reliability, scalability, monitoring, testing, and operational excellence through automation and continuous improvement.

Requirements

• At least 8 years of experience in data engineering, software engineering, or a related data-focused technical role.
• Proven ability to partner with business, product, and technical stakeholders to deliver scalable data solutions and platform capabilities.
• Expert-level Python and SQL skills, including experience building modular, testable, production-grade software.
• Strong experience designing analytical data models, semantic layers, shared metrics, and reusable data products.
• Deep expertise with cloud data platforms such as Snowflake, Databricks, or similar modern data ecosystems.
• Experience building scalable batch and streaming data pipelines in enterprise environments.
• Proficiency with orchestration and transformation frameworks such as Airflow, Dagster, Prefect, dbt, or comparable tools.
• Strong software engineering fundamentals, including object-oriented and functional programming methodologies.
• Understanding of modern AI architectures, including agent-based systems, retrieval patterns, semantic context modeling, knowledge representations, and enterprise data grounding.
• Experience building, supporting, or scaling enterprise data platforms used across multiple teams, products, or business domains.
• Strong product mindset and ability to identify reusable platform capabilities versus one-off solutions.
• Excellent written, verbal, and cross-functional communication skills.

Nice To Haves

• Knowledge of graphs, ontologies, metric stores, and other machine-readable representations of business context.
• Expertise in LLM applications, agent orchestration, retrieval pipelines, embeddings, vector search, and tool-calling architectures.
• Ability to evaluate AI systems for accuracy, consistency, security, and retrieval quality.

Responsibilities

• Partner with business stakeholders, product managers, and Engineering teams to understand data usage patterns, requirements, and unmet needs across critical workflows.
• Translate business needs into data product strategies, technical requirements, platform capabilities, and measurable outcomes.
• Design and maintain governed semantic models, business metrics, entities, and contextual frameworks for analytics, machine learning, and AI applications.
• Partner with Data Governance and domain owners to establish and enforce business definitions, ownership standards, calculations, and access policies.
• Collaborate with Analytics teams to make trusted and consistent metrics accessible for reporting, dashboards, predictive analytics, and operational decision-making.
• Build, automate, and optimize scalable data pipelines and platform infrastructure that support enterprise growth and data-driven decision-making.
• Develop reusable frameworks and components for data ingestion, transformation, modeling, quality management, and observability.
• Drive platform reliability, scalability, monitoring, testing, and operational excellence through automation and continuous improvement.

Benefits

• Equity for all full-time employees.
• Annual performance bonus.
• Employer-matched retirement plan.
• Comprehensive benefits package.
• Generously subsidized healthcare.
• 100% employer-paid dental, vision, telemedicine, and virtual mental health counseling.
• Parental leave.
• Unlimited paid time off (PTO).
• Flexible remote work on Fridays.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed