Lead Data Architect

We are seeking an experienced Data Architect with deep expertise in Databricks and a strong understanding of the insurance industry. The ideal candidate will design and implement scalable data architectures that support advanced analytics, reporting, and AI/BI/ML initiatives across Broking, Binding, underwriting, claims, actuarial, and policy management functions.

Key Responsibilities

Data Architecture & Strategy

• Design and implement enterprise data architecture leveraging Databricks Lakehouse, Delta Lake, and Azure cloud-native services
• Define data integration, modeling, and governance frameworks tailored for insurance data domains such as agency, carrier, policy, claims, Invoicing & billing, and reinsurance.
• Create scalable and secure data pipelines that handle structured and unstructured data from internal and external sources.
• Author and maintain technological roadmap with mappings to business capabilities
• Experiment and establish adoption blueprint for emerging capabilities within Databrick and in data technology
• Secure the data with appropriate NIST cyber controls
• Data Engineering & Analytics Enablement
• Lead the design of ETL/ELT pipelines using PySpark, SQL, Delta Live Tables, Lakeflow connect, Autoloader, Lake flow declarative pipelines, DBT, and Databricks Workflows.
• Partner with actuarial, underwriting, and BI teams to design semantic layers and analytics-ready datasets.
• Optimize performance and cost of Databricks clusters and workflows.
• Governance & Quality
• Review solution developed by the divisional teams and vendors to ensure the solution uses modern technology, built to scale, has resilience, and is cost effective to operate.
• Implement data quality, lineage, and metadata management frameworks using tools like Unity Catalog, Collibra, or Alation.
• Establish and enforce data security and compliance policies aligned with insurance regulations (e.g., NAIC, Privacy, HIPAA, GDPR, CFIUS).
• Ensure consistency of master data across operational and analytical systems.
• Collaboration & Leadership
• Collaborate with business leaders, data engineers, divisional data teams, data visualization experts, and platform head to align architecture with organizational goals.
• Mentor teams on best practices for data modeling, Databricks optimization, and cloud data architecture.
• Evaluate new technologies to continuously improve data strategy and capabilities.
• Required Qualifications:
• Bachelor’s or master’s degree in computer science, Data Engineering, Information Systems, or related field.
• 7 years of experience in data architecture or data engineering, with at least 4 years in Databricks.
• Strong experience with insurance data models, including policy, claims, premium, fees, agency, underwriting, accounting, and insured domains.
• Expertise in cloud platforms (AWS, Azure, or GCP) and modern data lakehouse architecture.
• Proficiency in SQL, PySpark, Delta Lake, and Databricks SQL.
• Experience integrating with BI tools (Power BI, Tableau, Looker) and data governance tools.
• Excellent communication and stakeholder management skills.
• Preferred Skills:
• Experience with streaming data frameworks (Kafka, Delta Live Tables).
• Familiarity with AI/ML pipelines in Databricks.
• Certification(s):
• Databricks Certified Data Engineer Professional
• Azure/AWS Certified Data Architect
• Insurance Data Management Association (IDMA) certifications
• Enable machine learning and predictive analytics by providing clean, governed, and feature-rich data sets.
  

**We are an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, color, ethnic origin, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.**