Description

What to Expect

The Sr. Data Warehouse Architect defines and governs enterprise data architecture across data warehouse, transactional, analytical, and near-real-time environments. This role leads complex architecture decisions, establishes enterprise standards, and ensures scalable, secure, and high-performing data solutions aligned with business, technology, and regulatory requirements.

What You Will Do

1. Enterprise Data Architecture Strategy and Design
• Define and evolve enterprise data architecture, target-state designs, and integration patterns across warehouse, lakehouse, transactional, and analytical platforms.
• Lead architecture decisions for complex, cross-functional initiatives to ensure solutions are scalable, secure, resilient, and aligned with business and technology strategy.
• Establish standards for data modeling, storage design, integration patterns, and workload optimization across enterprise data domains.
• Evaluate and recommend technologies, tools, and frameworks that improve performance, flexibility, cost efficiency, and long-term maintainability.
• Serve as the senior architectural advisor to engineering, analytics, and business stakeholders on high-impact platform and design decisions.

2. Near-Real-Time and Streaming Architecture
• Design architecture for near-real-time and streaming data solutions that support time-sensitive operational and analytical use cases.
• Define architecture patterns for event-driven processing, change data capture, and hybrid batch/streaming data flows.
• Lead design of cloud-based data platforms using AWS services to support scalable and reliable data delivery.
• Establish standards for streaming, schema management, and processing models to support performance, consistency, and reuse.
• Resolve complex technical issues and architectural tradeoffs involving latency, reliability, scalability, and interoperability.

3. Governance, Standards, and Risk Alignment
• Define and enforce enterprise data architecture standards, naming conventions, metadata management practices, and data lineage requirements.
• Partner with governance, security, compliance, and risk teams to ensure architectures align with enterprise controls and regulatory requirements.
• Establish frameworks that promote data quality, consistency, traceability, and trusted use of enterprise data.
• Support architecture decisions related to platform modernization, data lifecycle management, privacy, and control environments.

Qualifications

What You Will Bring
• Minimum 8 years progressive experience in data architecture, data engineering, or related technical roles.
• Experience designing enterprise data warehouse, transactional, analytical, and near-real-time data architectures.
• Strong hands-on experience with AWS data services, including Redshift, RDS, S3, Glue, Apache Iceberg, Lake Formation, Athena, and related tools.
• Experience with Oracle and relational database design in complex enterprise environments.
• Experience designing streaming and near-real-time data architectures using Kafka, Kinesis, or similar technologies.
• Experience working in enterprise-scale cloud data environments within regulated industries.
• AWS certification(s) such as Solutions Architect, Data Analytics, or Database Specialty.
• Familiarity with CI/CD, infrastructure-as-code, and modern data platform delivery practices.
• Experience with event-driven microservices architectures and schema registries (Glue Schema Registry, Confluent Schema Registry).
• Experience with BI/reporting tools (OBIEE, Tableau, or similar).
• Bachelor's degree in Computer Science, Engineering, Technology or a related discipline.
• Strong knowledge of enterprise data architecture principles, including warehouse, lakehouse, transactional, and analytical platform design.
• Strong knowledge of data modeling, ETL/ELT architecture, data integration, and modern lakehouse design.
• Strong knowledge of cloud-native data platform architecture and AWS data services.
• Knowledge of near-real-time and streaming architecture patterns, including event-driven processing and change data capture.
• Strong understanding of data governance, metadata management, data lineage, and data cataloging.
• Knowledge of data privacy, security, and control requirements relevant to enterprise data architecture.
• Ability to analyze business and system requirements and design scalable, secure, and high-performing data solutions.
• Ability to evaluate architectural tradeoffs involving performance, latency, reliability, interoperability, and cost.
• Ability to work independently and influence cross-functional stakeholders on complex technical decisions.
• Strong verbal, written, and interpersonal communication skills.

Work Environment

Employees in this class are subject to extended periods of sitting, standing, and walking, vision to monitor and moderate noise levels. Work is performed in an at home and office environment.

The posted salary range for this job takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; geographic location, and other business and organizational needs. Successful candidates may be hired anywhere in the salary range based on these factors. It is uncommon to hire candidates at or near the top of the range.