Requirements

• 12-20 years of experience in enterprise data architecture, data strategy, and cloud architecture
• Expertise in operational data use cases: real-time data processing, APIs, messaging/streaming (Kafka, Pub/Sub, MQ), MDM, and transactional data flows
• Strong background in data modeling (conceptual, logical, physical) with a focus on domain-driven design (DDD)
• Proven ability to select, implement, and scale Master Data Management (MDM) solutions, including strategy definition, vendor assessment, and governance adoption
• Experience establishing reference data management and data quality practices at enterprise scale
• Knowledge of analytical data architectures: data lakes, warehouses (e.g., Snowflake, BigQuery), BI/reporting, and ETL pipelines
• Proficiency in public cloud platforms (AWS, Google Cloud Platform, Microsoft Azure)
• Experience with both transactional RDBMS and modern distributed/cloud-native databases
• Familiarity with reporting and analytics tools (e.g., Tableau, Data Studio, Business Objects, Cognos, R)
• Skilled in architecture methodologies such as TOGAF
• Excellent communication, stakeholder management, and leadership skills
• Bachelor’s degree in engineering, Computer Science, or related field (Master’s preferred) Professional certifications such as CDMP (DAMA), Google Cloud Professional Cloud Architect, Microsoft Certified: Azure Solutions Architect Expert, or equivalent

Responsibilities

• Define and implement enterprise data architecture, ensuring alignment with both operational and analytical business needs
• Lead domain-driven data modeling efforts across conceptual, logical, and physical layers to ensure data designs reflect business domains and processes
• Define and oversee Master Data Management (MDM) strategies, including tool selection, vendor evaluation, implementation, and adoption across the enterprise
• Establish and maintain reference data management frameworks and governance processes
• Develop and execute data strategies, including future state architecture, data governance, metadata management, data privacy, reference data management, and data integration
• Lead the design and review of data architectures for both operational platforms (APIs, event streams, transactional systems) and analytical platforms (data lakes, warehouses, reporting)
• Establish and enforce data architecture standards, principles, and best practices across operational and analytical domains
• Drive adoption of governance frameworks, data quality practices, and remediation of technical debt
• Collaborate with application, integration, and analytics teams to deliver end-to-end data solutions
• Evaluate and select tools for operational integration (streaming, APIs, MDM) and analytical processing (warehouses, BI platforms)
• Design and maintain conceptual, logical, and domain models spanning both transactional and analytical data
• Mentor and guide teams in data architecture, integration, and business intelligence best practices