Principal Data Architect

Responsibilities

• Data Lakehouse and Warehouse Architecture: Own reference architectures and design patterns for enterprise data Lakehouse and warehouse platforms, including AWS Redshift, Apache Iceberg, Oracle Exadata, S3, Glue, Lake Formation, Athena, EMR, Presto, Airflow, and related ecosystem capabilities.
• Architecture Standards and Reuse: Create and maintain data architecture principles, design standards, reusable patterns, architecture decision records, reference implementations, and best-practice guidance that can be adopted across programs.
• Real-Time and Batch Data Architecture: Define patterns for both batch and real-time data movement, including Kafka schemas, event-driven design, data contracts, schema governance, replication, CDC, ETL/ELT, medallion architecture layers, and data quality controls across pipelines.
• Governance, Metadata, Lineage, and Data Quality: Partner with Enterprise Data Management and governance teams to embed metadata, lineage, data quality, cataloging, ownership, privacy classification, retention, and stewardship expectations into platform and solution architecture.

Requirements

• Must have deep, hands-on experience in wealth management , asset management, brokerage, private client services, or closely related financial services domains.
• Proven ability to influence senior stakeholders, guide complex architectural decisions, mentor architects or senior engineers, and lead through ambiguity.
• Expert level knowledge of Data Architecture, Data Modeling, Data Lake house and data warehouse design methodologies (star schema, snowflake schema, normalization, denormalization).
• Proficient with database technologies: Oracle (including RAC, Exadata), SQL Server, AWS Redshift, and replication tools like Oracle Golden Gate and AWS DMS.
• Advanced SQL, PL/SQL development, and database performance tuning skills.
• Deep expertise in AWS Data Ecosystem-Athena, Iceberg, Lake Formation, Glue, EMR, Sagemaker, S3, Airflow, Aurora, Presto.
• Skilled in scripting and automation (Shell, Python).
• Data integration architecture: Ability to architect ETL/ELT, streaming, event-driven, API-based, file-based, and replication-based data flows, including data contracts, schema evolution, lineage, quality checks, and operational monitoring.
• Data Lakehouse & Data Marketplace Architecture: Proven experience designing and operationalizing enterprise-scale data lake, Lakehouse, or data marketplace platforms, including governed data onboarding, metadata management, data product publishing.
• AI Data Readiness & Semantic Data Enablement: Demonstrated ability to assess, structure, and curate enterprise data for AI, advanced analytics, and GenAI use cases, including defining semantic models, ontologies, knowledge graphs.
• Education/Previous Experience:
• Bachelor's degree in Computer Science, MIS, or related

Benefits

Additional Information

Job Description Summary The Principal Data Architect is a senior enterprise architecture and strategy leader within the Enterprise Data & Analytics Architecture team. This role defines and advances the enterprise data architecture vision, target-state patterns, data platform strategy, and adoption roadmap across on-premises and cloud environments. The Principal Data Architect partners with senior technology leaders, data engineering teams, enterprise data management, analytics consumers, security, risk, compliance, and business stakeholders to deliver scalable, secure, reusable, and business-aligned data capabilities. Job Description This position follows our hybrid-friendly schedule, so you get the best of both worlds - flexibility and collaboration. In office days will be 2-3 per week averaging 10-12 days per month in our St Petersburg, FL Corporate Office.

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