Snowflake Data Platform Lead | Data Eng & Governance

Willis Re Inc; New York (NY); On-site; USD 160,000 - 180,000; Full time

Benefits offered by this job

Health insurance

401(k) savings and retirement programs

Paid time off

Employee assistance programs

Job summary

Willis Re Inc is building its global data estate with a Snowflake‑driven platform and seeks a Data Engineering Lead to drive implementation and governance. You will work hands‑on on ingestion, modelling and tagging, while defining data quality, lineage and cost‑aware architecture.

You will mentor engineers, partner with security and business stakeholders, and shape the data platform to scale for high‑volume reinsurance data.

Qualifications

• 10+ years in data engineering with end-to-end platform delivery.
• Hands-on Snowflake expertise across warehouse sizing, RBAC, ingestion, sharing.
• Strong governance: tagging, catalogues, lineage, access policies.
• Proven data quality, automated testing and monitoring.
• Deep data modelling, high-volume warehouse design and cost control.
• SQL & Python mastery; CI/CD and IaC on Azure.

Responsibilities

• Snowflake development: architecting the platform, ingestion and models.
• Establish tagging, cataloguing and governance for discoverable data.
• Own data governance, lineage, retention and cross-border residency.
• Define data quality controls, monitoring and reconciliation.
• Design scalable architecture with partitioning, archival strategy.
• Lead vendor work, enforce standards and review designs.
• Set CI/CD, observability and infrastructure-as-code practices.
• Mentor engineers and grow the data engineering team.

Skills

Snowflake

Data governance

Data quality

SQL

Python

CI/CD

Azure

Leadership

Vendor management

Terraform

Tools

dbt

Snowflake Cortex AI

Claude Code

Terraform

Azure DevOps

GitHub Actions

Job description

Willis Re Inc is building its global data estate with a Snowflake‑driven platform and seeks a Data Engineering Lead to drive implementation and governance. You will work hands‑on on ingestion, modelling and tagging, while defining data quality, lineage and cost‑aware architecture.

You will mentor engineers, partner with security and business stakeholders, and shape the data platform to scale for high‑volume reinsurance data.