Senior Enterprise Data Architect

Senior Enterprise Data Architect (Hands-On, Databricks Focus)

Our client, a leading enterprise organization in the insurance sector, is seeking a senior-level Data Architect to help define and advance the future state of its enterprise data ecosystem. This individual will play a pivotal role in shaping the architectural direction of the organization’s data platforms, ensuring that data is structured, integrated, and accessible to support operational excellence, analytics, and digital transformation initiatives.

This is a highly hands-on architectural role focused on designing and enabling a modern data environment centered around Databricks. All enterprise data flows into the Databricks platform, and this architect will help ensure data is properly structured, integrated, and aligned to support scalable data products—particularly those built around core policy and insurance domain data.

Unlike prior leadership roles in this area, this position does not include direct people management. Instead, the focus is on hands-on architecture, technical leadership, and enterprise-wide influence through collaboration with enterprise architecture, data engineering, integration teams, and platform stakeholders.

The ideal candidate combines strategic architectural vision with practical implementation experience and can operate at the enterprise level—understanding both the broader ecosystem and the technical foundations required to support it.

Key Responsibilities

Enterprise Data Architecture and Strategy

• Define and evolve the enterprise data architecture, ensuring alignment with current business needs and long-term strategic goals.
• Help establish the future-state vision for the organization’s data ecosystem, with Databricks serving as the central data platform.
• Design scalable architectural patterns that support data product development, particularly around policy and core insurance domain data.
• Assess the current data landscape, including data sources, flows, integrations, and platform dependencies, and recommend architectural improvements.
• Develop architectural standards, integration patterns, and best practices to ensure consistency, scalability, and maintainability.

Databricks-Centered Platform Architecture

• Architect and optimize enterprise data pipelines and integration frameworks that ingest, transform, and deliver data into Databricks.
• Design and maintain logical and physical data models aligned with lakehouse architecture principles.
• Ensure efficient, reliable, and scalable data ingestion and transformation processes across batch and real-time workflows.
• Partner closely with the Databricks platform team to ensure optimal performance, governance, and platform utilization.
• Support the evolution of modern lakehouse capabilities that enable analytics, reporting, and advanced data consumption.

Enterprise Integration and Ecosystem Alignment

• Collaborate with enterprise architecture, data engineering, and integration teams to ensure cohesive and scalable data solutions.
• Ensure data architecture aligns with broader enterprise technology standards and architectural direction.
• Define and guide integration strategies between operational systems, enterprise platforms, and centralized data environments.
• Enable consistent and reliable data access across business, analytics, and operational teams.

Stakeholder Engagement and Technical Leadership

• Serve as a key architectural voice in defining enterprise data strategy and platform direction.
• Communicate architectural vision, technical strategy, and platform capabilities to internal stakeholders across business and technology teams.
• Translate complex business and technical requirements into scalable, maintainable architectural solutions.
• Provide technical leadership and guidance without direct people management responsibilities.
• Help drive architectural alignment across multiple concurrent data initiatives and transformation efforts.

Required Qualifications

• 12 years of experience in data architecture, data engineering, or enterprise data platform roles.
• Proven experience operating at the enterprise level, designing and evolving large-scale data ecosystems.
• Strong experience architecting modern data platforms, data lakes, or lakehouse environments.
• Hands-on experience with Databricks strongly preferred; Snowflake or similar modern cloud data platforms may be considered for the right candidate.
• Deep understanding of enterprise data flows, integration patterns, and ecosystem design.
• Strong expertise in data modeling, data integration, ETL/ELT design, and distributed data systems.
• Experience reviewing and optimizing existing data environments and defining future-state architecture.
• Strong SQL and data engineering fundamentals.
• Experience collaborating with enterprise architecture, platform teams, and cross-functional stakeholders.
• Ability to balance strategic architectural thinking with practical implementation considerations.
• Excellent communication skills, with the ability to articulate technical vision and influence stakeholders across the organization.

Preferred Qualifications

• Experience working within the insurance industry or other regulated enterprise environments.
• Experience designing or supporting data products built around core business domains such as policy, claims, or customer data.
• Experience supporting Databricks lakehouse implementations at enterprise scale.
• Background evolving from senior individual contributor roles into enterprise-level architectural leadership positions.
• Experience defining architectural standards in complex, multi-platform enterprise environments.
• Familiarity with cloud-native data architectures and modern data engineering practices.

Role Overview

This role is ideal for a senior Data Architect who thrives in a hands-on, high-impact environment and wants to help shape the strategic direction of a modern enterprise data ecosystem. The successful candidate will play a critical role in aligning current data capabilities with the organization’s long-term vision, ensuring Databricks and related platforms enable scalable, reliable, and future-ready data solutions.

Salary: $215,000-$225,000/year

Compensation is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications.