We are seeking an experienced Data Platform Architect / Data Warehouse Architect to lead enterprise data platform architecture, modernization, strategy, and innovation initiatives. The ideal candidate will have strong experience developing enterprise data strategies, target-state architectures, data platforms, data/analytics/ML products, and architecture standards using frameworks such as TOGAF, FEAF, or DODAF.
The architect will work closely with Enterprise Architects, Data Architects, engineering teams, analytics teams, security teams, business stakeholders, and technology vendors to establish modern Enterprise Data Platform (EDP) capabilities and support data-driven business strategies.
Required Skills & Qualifications
5+ years of experience leading Data Architects and collaborating with Enterprise Architects to develop:
Enterprise Data Landscapes
Data Strategies
Data Architectural approaches
Target-state data architectures
Experience aligning data, business, application, and technology landscapes to support enterprise data-driven strategies.
5+ years of experience developing Reference Architectures and Architecture Pattern Libraries.
5+ years of experience conducting architectural reviews, identifying architectural exceptions, and managing exceptions to maintain enterprise data platform integrity.
3+ years of experience driving RFI/RFP processes for selecting data platform technologies.
Experience partnering with technology vendors to co-develop innovative Enterprise Data Platform capabilities.
Experience driving data platform innovation and promoting data-driven decision-making through Communities of Practice and similar initiatives.
Bachelor's degree in Computer Science, Data Science, Information Systems, or a related computer science field.
Strong experience with modern Enterprise Data Platforms and data warehouse architecture.
Experience with Data Lake, Delta Lake, EDP, Data Warehousing, and Databricks.
Technical Skills
Programming: SQL, Python, R, Java
Architecture: TOGAF, FEAF, DODAF
Data Platforms: Enterprise Data Platform (EDP), Data Lake, Delta Lake, Data Warehousing, Data Marts
Databases: SQL/Relational, NoSQL, GraphDB
Cloud/Data Technologies: Databricks and cloud-based data services
Analytics & Visualization: Power BI, Tableau
Data Architecture: Operational Data Stores, ETL/ELT, metadata management, data profiling, performance monitoring
Key Responsibilities
Design and maintain the overall architecture for enterprise data platforms, ensuring scalability, reliability, security, and alignment with business objectives.
Develop target-state Data Platform Architecture aligned with enterprise data strategy and business outcomes.
Track emerging industry capabilities and recommend modern data technologies and cloud services.
Design, architect, and support Data, Analytics, and Machine Learning products.
Oversee implementation of modern data platform components, including storage, streaming, orchestration, integration, and analytics services.
Ensure data platform components function cohesively as an integrated enterprise solution.
Establish and maintain governance frameworks covering:
Data quality
Data security
Metadata management
Data sharing
Regulatory and organizational compliance
Embed data governance standards into Data Engineering products, pipelines, Analytics/ML products, and related solutions.
Enforce Data Security standards and best practices throughout data products and pipelines.
Collaborate with engineering, analytics, security, architecture, and business teams to translate strategic requirements into technical solutions and roadmap initiatives.
Design and maintain Data Services Portfolios and enterprise Data Products based on industry best practices.
Recommend and lead adoption of emerging cloud-based data services, analytical tools, and modern technologies.
Support data warehouse and analytics platform modernization initiatives.
Select appropriate hardware, software, tools, and lifecycle techniques for data warehouse components, including ETL, metadata, data profiling, monitoring, reporting, and analytics.
Drive Proofs of Concept (POCs), Codathons, technology evaluations, and vendor co-development initiatives.
Lead POC execution to evaluate emerging technologies and support enterprise technology decisions.
Establish fully functioning Enterprise Data Platform environments supporting Data Engineering teams and operational Data/Analytics/ML pipelines.
Drive procurement activities, including RFI/RFP processes, for selecting Cloud Service Providers and data platform technologies.
Develop Data Engineering standards, methodologies, best practices, and architectural guidelines.
Monitor architectural adherence of Data Engineering products and pipelines to enterprise standards.
Support Data Engineering teams in improving capability maturity and delivering high-quality data products.
Help ensure POCs, early implementations, legacy technology refreshes, and modernization efforts align with the enterprise target architecture and long-term strategy.
Highly Desired
Experience supporting enterprise Data Engineering teams in building and maturing technical and delivery capabilities.
Experience tracking architectural adherence of Data Engineering products and pipelines against Enterprise Architecture standards and best practices.
Experience with Databricks, Delta Lake, Data Lakes, Enterprise Data Platforms, and modern cloud data architectures.
Experience with cloud-based data warehouse and analytics modernization.
Experience with data governance, data security, metadata management, and regulatory compliance.
Experience working with technology vendors and leading enterprise-level technology evaluations and POCs.
Additional Requirement
Candidates must provide 2 professional references. Please attach the references as a separate document.
