Key Responsibilities:

• Data Architecture Design:
  Develop and maintain an enterprise-wide data architecture, aligning with business goals and IT strategies. Design efficient database solutions to store and retrieve data securely.
  
• Data Modeling & Database Design:
  Create and optimize data models (conceptual, logical, and physical) for both transactional and analytical systems. Ensure data accuracy, consistency, and scalability across systems.
  
• Data Integration & ETL Processes:
  Define and implement data integration strategies, including ETL processes to extract, transform, and load data from various sources into centralized databases or data lakes.
  
• Data Governance:
  Establish and enforce data management policies, including data quality, security, and privacy standards. Ensure compliance with relevant data regulations (GDPR, CCPA, etc.).
  
• Collaboration with Stakeholders:
  Work closely with business analysts, data engineers, data scientists, and other stakeholders to translate business requirements into data architecture solutions. Provide guidance on data-related technical issues and best practices.
  
• Technology Evaluation:
  Evaluate and recommend appropriate database and data storage technologies, ensuring they align with organizational needs. Stay current with emerging trends in data architecture and big data technologies.
  
• Data Security & Privacy:
  Design and implement secure data management systems that ensure data integrity, confidentiality, and protection against unauthorized access.
  
• Performance Optimization:
  Monitor and optimize the performance of data systems, identifying areas for improvement and ensuring systems meet performance requirements.
  
• Documentation & Standards:
  Maintain thorough documentation of data architecture designs, models, and processes. Define and enforce data standards and best practices across the organization.
  

Requirements:

• Education:
  Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field.
  
• Experience:
  
  • Minimum of 5 years of experience in data architecture, database design, or data engineering roles.
  • Proven experience with data modeling, database management systems (RDBMS, No SQL), and data warehousing solutions.
• Skills & Expertise:
  
  • Expertise in data modeling techniques (ERD, UML) and data management tools (e.g., ER/Studio, Erwin).
  • Hands-on experience with cloud platforms and cloud-native database services.
  • Proficiency with SQL, No SQL, and data integration technologies (ETL tools, APIs).
  • Knowledge of big data technologies (Hadoop, Spark, Kafka) is a plus.
  • Strong understanding of data governance frameworks and best practices.
  • Familiarity with BI tools (e.g., Power BI, Tableau) and data analytics frameworks.
• Preferred Qualifications:
  
  • Experience with machine learning models and AI-driven data platforms.
  • Certification in cloud-based data services (e.g., AWS Certified Data Analytics, Microsoft Azure Data Engineer).