Lead the architectural vision for data platform modernization initiatives. This role involves defining comprehensive migration strategies and owning the target state architecture across the entire data lifecycle, from ingestion to consumption.

You will be instrumental in shaping how data is managed, processed, and leveraged, ensuring alignment with enterprise standards, security, and governance.

Key to this role is the design and implementation of advanced data solutions, including Databricks and Snowflake, to meet complex business needs.

Define end-to-end data platform migration strategies, encompassing data ingestion, storage, transformation, and consumption.

Own the target state architecture, ensuring robust data processing, security, and observability.

Develop detailed architecture diagrams, migration plans, and reference patterns.

Align architectural designs with enterprise standards, security protocols, and cloud governance.

Design Databricks architecture, including workspaces, clusters, Delta Lake layers, and Azure service integrations.

Establish canonical migration patterns for tables, stored procedures, and data loading mechanisms.

Create reusable migration frameworks and accelerators to streamline the modernization process.

Implement a wave-based migration model with clear entry and exit criteria.

A minimum of 15 years of experience in designing enterprise data platforms, Lakehouse/medallion architectures, and scalable analytics ecosystems, preferably within regulated industries.

Demonstrated expertise in defining Bronze, Silver, and Gold/ODS patterns using Databricks, ADLS/S3, Delta Lake, DBT, orchestration tools, and secure consumption layers.

Strong proficiency in canonical data modeling across critical business domains such as Policy, Claims, Billing, and Customer.

Proven ability to make architecture decisions regarding performance, partitioning, lineage, metadata management, resilience, and disaster recovery.

Capability to align enterprise standards, security controls, DevSecOps practices, and future extensibility for AI/ML and self-service analytics.