Senior Insurance Data Architect

Job Overview

• ">
• A strategic data architect will design and implement a cutting-edge analytics platform to support business growth.">

Responsibilities

• ">
• Design and deploy end-to-end data architectures for cross-product reporting solutions, including lakehouse/warehouse, streaming + batch pipelines, semantic layer, and BI.">
• Develop a comprehensive insurance data model encompassing policy, rating, endorsements, claims, billing, receivables/payables, and broker accounting, along with conformed dimensions (party, product, coverage, risk unit, geography, time).">
• Establish robust data contracts and versioned schemas with product teams; drive event standards for policy lifecycle, claims, and accounting events.">
• Implement multi-tenant data isolation and security strategies, including workspace, schema, and row-level controls; enforce RBAC/ABAC, encryption, and key management aligned to industry standards.">
• Build the ingestion and transformation layer: streaming (Kafka/Event Hubs) and batch (ELT/ETL) into a bronze/silver/gold model; manage SCD, late-arriving data, and idempotency.">
• Establish the semantic layer (e.g., Power BI/Fabric/Looker semantic models) with governed, reusable metrics.">
• Institute data quality and observability checks, SLAs/SLOs, lineage, and monitoring (contracts, schema drift, nullability, referential integrity, reconciliation to source).">
• Own governance & compliance: metadata, lineage, catalog, PII handling, retention, audit trails; champion Purview (or equivalent) and data stewardship processes.">
• Drive performance, reliability & cost optimization through partitioning/clustering, query acceleration, workload management, caching, workload isolation, and cost guardrails.">
• Publish 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; run data design reviews with product squads; mentor data engineers/analysts.">
• Release management for data: CI/CD for pipelines/models, automated tests (unit/data tests), backward-compatible schema versioning, and environment promotions.">
• Collaborate 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 standards (SOC 2/GDPR/PCI-DSS).">
• Excellent communication and stakeholder management; ability to run design reviews and mentor teams.">

Desirable Qualifications and Skills

• ">
• Knowledge of reinsurance, bordereau reporting, and regulatory/data-sharing requirements.">
• Familiarity with DAMA-DMBOK practices and metric standardization frameworks.">
• Certifications in Azure Data, Databricks, or Power BI; Agile experience.">