Data Platform Architect / Data Warehouse Architect

Job Description

We are seeking an experienced Data Platform Architect / Data Warehouse Architect to design and drive modernization of enterprise data platforms, data warehouses, analytics environments, and data engineering capabilities. The ideal candidate will have strong experience developing enterprise data strategies, target-state architectures, cloud data platforms, data governance, data security, and Data/Analytics/ML products.

The candidate will work closely with engineering, analytics, security, business, and architecture teams to develop scalable, secure, governed, and high-performing enterprise data solutions aligned with organizational business objectives.

Required Qualifications

• Bachelor s degree in Computer Science, Data Science, Information Systems, or a related field.

• 5+ years of experience in enterprise data architecture, data platform architecture, data warehousing, or data engineering architecture.

• Strong experience developing Enterprise Data Technology Strategies, target-state data architectures, and data engineering standards and best practices.

• Experience with Data Engineering Delivery Methodologies and establishing standards to align Data, Analytics, and ML products with enterprise architecture.

• Experience with enterprise architecture frameworks such as TOGAF, FEAF, DoDAF, or similar frameworks.

• Demonstrated experience evaluating and adopting emerging data technologies through Proofs of Concept (POCs), technical evaluations, vendor collaboration, and co-development initiatives.

• Strong understanding of the full technology stack of modern Enterprise Data Platforms, including cloud storage, databases, data integration, ETL/ELT, orchestration, streaming, analytics, metadata, governance, monitoring, and security.

• Experience establishing and operationalizing cloud-based Enterprise Data Platforms to support data engineering, analytics, and ML pipelines.

• Demonstrated experience supporting or leading RFI/RFP/procurement processes for enterprise data platforms and Cloud Service Provider (CSP) selection.

• Experience architecting Data Services Portfolios and Data Products based on business requirements, industry standards, and organizational capabilities.

• Strong knowledge of implementing Data Governance, Data Quality, Metadata Management, Master Data, and Data Lifecycle Management practices.

• Demonstrated experience incorporating data security standards and best practices into data platforms, data products, analytics environments, and data pipelines.

• Strong understanding of regulatory, compliance, privacy, and security requirements related to enterprise data environments.

Roles and Responsibilities

• Design, develop, and maintain the overall architecture for enterprise data platforms and data warehouse environments, ensuring scalability, reliability, performance, security, and alignment with business objectives.

• Develop target-state data platform architectures, roadmaps, reference architectures, and technology strategies.

• Lead data platform modernization initiatives involving cloud-based data services, analytical technologies, data engineering tools, and emerging technologies.

• Evaluate emerging technologies and lead Proofs of Concept, technical pilots, vendor evaluations, and co-development initiatives to support enterprise technology decisions.

• Oversee implementation of modern data platform components, including data storage, databases, data integration, ETL/ELT, streaming, orchestration, metadata, analytics, monitoring, and reporting services.

• Establish and maintain enterprise data engineering standards, architecture patterns, best practices, and development methodologies.

• Design and support scalable Data, Analytics, and Machine Learning pipelines and products.

• Architect and maintain enterprise Data Services Portfolios and Data Products aligned with organizational strategy and data capabilities.

• Establish and enforce data governance frameworks covering data quality, metadata, security, privacy, compliance, lineage, and data lifecycle management.

• Ensure data security standards and best practices are embedded throughout the data platform, pipelines, applications, analytics solutions, and ML products.

• Collaborate with data engineers, developers, data scientists, analysts, cybersecurity teams, business stakeholders, and enterprise architects to translate business requirements into technical solutions.

• Develop technical roadmaps and modernization strategies for data warehouse and analytics environments.

• Support the selection of appropriate hardware, software, cloud services, platforms, tools, and system lifecycle approaches for enterprise data architecture components.

• Provide architecture guidance for ETL/ELT, data profiling, metadata management, data quality, performance monitoring, reporting, analytics, and data visualization technologies.

• Evaluate platform performance, scalability, reliability, and sustainability and recommend improvements.

• Support vendor management, technology evaluations, procurement activities, and technical reviews associated with enterprise data platforms.

• Establish processes that promote the adoption and effective use of enterprise data engineering products across the user and development community.

• Identify architecture, implementation, security, governance, and performance risks and develop mitigation strategies.

• Ensure data platform solutions comply with applicable organizational, regulatory, privacy, security, and data governance requirements.