Data Engineering Lead

Solution Architect Role

A cross-product reporting solution is required to be led by a Solution Architect. This role encompasses data architecture, streaming and batch pipelines, semantic layer, and business intelligence.

Key Responsibilities

1. Owning end-to-end data architecture for a cross-product reporting solution, including lakehouse/warehouse, streaming + batch pipelines, semantic layer, and BI.
2. Defining 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).
3. Establishing robust data contracts and versioned schemas with product teams; driving event standards for policy lifecycle, claims, and accounting events.
4. Designing multi-tenant data isolation and security, including workspace, schema, and row-level strategies; enforcing RBAC/ABAC, encryption, and key management aligned to SOC 2, GDPR, and PCI-DSS.
5. Building the ingestion and transformation layer: streaming (Kafka/Event Hubs) and batch (ELT/ETL) into a bronze/silver/gold (medallion) model; managing SCD, late-arriving data, and idempotency.
6. Standing up the semantic layer (e.g., Power BI/Fabric/Looker semantic models) with governed, reusable metrics.
7. Instituting data quality and observability: checks, SLAs/SLOs, lineage, and monitoring (contracts, schema drift, nullability, referential integrity, reconciliation to source).
8. Owning governance & compliance: metadata, lineage, catalog, PII handling, retention, audit trails; championing Purview (or equivalent) and data stewardship processes.
9. Driving performance, reliability & cost: partitioning/clustering, query acceleration, workload management, caching, workload isolation, and cost guardrails.
10. 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).
11. Enabling reference implementations, style guides, model playbooks; running data design reviews with product squads; mentoring data engineers/analysts.
12. Release management for data: CI/CD for pipelines/models, automated tests (unit/data tests), backward-compatible schema versioning, and environment promotions.

The ideal candidate will have a Bachelor's or Master's degree in computer science, engineering, or a related field, along with 12+ years of experience in data engineering/architecture and 5+ years of architecting analytics platforms for SaaS or enterprise products.

Strong dimensional/star schema and semantic modeling skills are required, along with 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 is also necessary.

A deep understanding of insurance data, including policy lifecycle, coverages/endorsements, claims, premiums, reserves, bordereaux, and broker accounting, is essential.

Requirements

• Experience in leading cross-functional teams
• Expertise in data architecture and engineering
• Familiarity with Azure data stack and Power BI
• Strong dimensional and star schema skills
• Understanding of insurance data and policies

Benefits

We offer a dynamic work environment, competitive salary, and opportunities for professional growth and development.

Contact Us

Please submit your application, including your resume and a cover letter, to us.