Azure Enterprise Principal Architect--Need Local or Near-by--F2F Mandate

Title: Azure Enterprise Principal Architect

Location: Atlanta, GA—Hybrid—Need Local or Near-by—F2F Mandate

Duration: Long Term

Platform & Technology Leadership:

·         Serve as the principal architect for Databricks — Unity Catalog, Delta Live Tables, Workflows, and the emerging LTAP (Lakebase) architecture for AI agent workloads.

·         Architect real-time and batch data pipelines using Databricks, dbt, and streaming technologies (Apache Kafka / Spark Structured Streaming).

·         Evaluate and govern the adoption of complementary tools in the modern data stack (Fivetran, dbt, data catalog, reverse ETL, semantic layer).

·         Define cloud infrastructure architecture patterns on Azure or AWS supporting the Databricks environment, ensuring scalability, cost governance, and HA/DR.

Data Governance & Compliance

·         Architect enterprise data governance frameworks aligned with banking regulations: BSA/AML, CCPA, GLBA, Basel III/IV, and OCC model risk guidelines.

·         Design and implement data lineage, data quality, and master data management (MDM) capabilities across the merged institution.

·         Partner with Legal, Risk, and Compliance to ensure data handling architecture meets audit, privacy, and regulatory reporting requirements.

·         Establish data classification and access control patterns within Unity Catalog to enforce row-level and column-level security at scale.

Required Qualifications:

·         Experience at a bank, fintech, or financial services firm with $50B+ in assets.

·         Familiarity with banking data domains: core banking systems, loan origination, deposit systems, general ledger, and regulatory reporting (CCAR, DFAST, Call Report).

·         Databricks Certified Data Engineer Associate/Professional or equivalent certification.

·         Experience with dbt (data build tool), Apache Kafka, or Confluent for streaming data pipelines.

·         Exposure to AI/ML platform architecture — MLflow, Feature Store, AI agents in Databricks.

·         10+ years of data architecture, data engineering, or data platform experience in large, complex organizations.

·         5+ years of hands-on experience with Databricks — including Delta Lake, Unity Catalog, Databricks SQL, and Databricks Workflows.

·         Deep expertise in data modeling: dimensional modeling, Data Vault 2.0, entity-relationship design, and domain-driven data products.

·         Strong proficiency in SQL and Python; familiarity with PySpark and Databricks notebooks.

·         Experience architecting lakehouse solutions on cloud platforms (Azure preferred; AWS acceptable).

·         Demonstrated experience with data governance frameworks — data lineage, catalog, quality, MDM, and access control.