Chief Data Architect

About the Role

We are seeking an experienced Data Architect Leader to spearhead our data architecture initiatives. The ideal candidate will have a strong background in designing and implementing scalable lakehouse/warehouse architectures, event-driven data pipelines, and semantic modeling.

Key Responsibilities:

• Oversight of end-to-end data architecture for cross-product reporting solutions (lakehouse/warehouse, streaming + batch pipelines, semantic layer, and BI).
• Development of a canonical insurance data model spanning policy, rating, endorsements, claims, billing, receivables/payables, and broker accounting—plus conformed dimensions (party, product, coverage, risk unit, geography, time).
• Establishment of robust data contracts and versioned schemas with product teams; driving event standards for policy lifecycle, claims, and accounting events.
• Design of multi-tenant data isolation and security strategies, including workspace, schema, and row-level controls; enforcement of RBAC/ABAC, encryption, and key management aligned to industry standards.
• Building the ingestion and transformation layer: streaming (Kafka/Event Hubs) and batch (ELT/ETL) into a bronze/silver/gold (medallion) model; management of SCD, late-arriving data, and idempotency.
• Standalone semantic layer (e.g., Power BI/Fabric/Looker semantic models) with governed, reusable metrics.
• Institutionalization of data quality and observability: checks, SLAs/SLOs, lineage, and monitoring (contracts, schema drift, nullability, referential integrity, reconciliation to source).
• Oversight of governance & compliance: metadata, lineage, catalog, PII handling, retention, audit trails; championing Purview (or equivalent) and data stewardship processes.
• Driving performance, reliability & cost optimization: partitioning/clustering, query acceleration, workload management, caching, workload isolation, and cost guardrails.
• Publishing the tooling roadmap: Azure-native and complementary tools (ADLS Gen2/Fabric or Databricks + Delta, Synapse/Fabric pipelines, Azure SQL/PostgreSQL, Purview, Key Vault, Power BI).
• Enablement: reference implementations, style guides, model playbooks; running data design reviews with product squads; mentoring data engineers/analysts.
• Release management for data: CI/CD for pipelines/models, automated tests (unit/data tests), backward-compatible schema versioning, and environment promotions.
• Collaboration with Product, Engineering, and Implementation to prioritize analytics use cases and deliver roadmaps tied to customer outcomes.

Requirements

• Bachelor's or Master's degree in computer science, engineering, or a related field.
• 12+ years in data engineering/architecture, with 5+ years architecting analytics platforms for SaaS or enterprise products.
• Proven experience designing lakehouse/warehouse architectures and event-driven data pipelines at scale (Kafka/Event Hubs).
• Strong dimensional/star schema and semantic modeling; familiarity with Data Vault and canonical modeling patterns.
• Expertise with Azure data stack (ADLS Gen2, Fabric or Databricks + Delta, Synapse/Fabric pipelines, Azure SQL/PostgreSQL, Purview, Key Vault) and Power BI.
• Deep understanding of insurance data (policy lifecycle, coverages/endorsements, claims, premiums, reserves, bordereaux, broker accounting).
• Hands-on with Python/SQL; CI/CD for data (tests, orchestration, IaC/DevOps).
• Grounding in data governance, lineage, and security (RBAC/ABAC, PII, encryption, retention); experience with industry-standard controls.
• Excellent communication and stakeholder management; ability to run design reviews and mentor teams.

Benefits

By joining our team, you'll have the opportunity to work on cutting-edge projects, collaborate with top talent, and contribute to the development of innovative data solutions.

Others

Please submit your application, including your resume and a cover letter outlining your relevant experience and qualifications.