Requirements:
- At least 10 years of experience in IT or Software Engineering
- Proven experience as a Data Architect or in a similar role, with a strong track record of designing and implementing transactional and analytical data architectures.
- Proficient in data modeling techniques, data integration methodologies, and data management principles.
- Extensive knowledge of database systems, modern data warehousing, data lake and data storage technologies.
- Experience with cloud-based data platforms and technologies (e.g., Azure, AWS, GCP) is essential.
- Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
- Highly detail oriented with excellent communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at all levels.
- Familiarity with data governance, data security, and data privacy regulations.
- Good understanding of data protection standards and associated security processes.
Data Strategy and Architecture:
- Develop and maintain the company's data strategy, ensuring alignment with business goals and objectives.
- Design, implement, and oversee the overall data architecture, including data integration, data modeling, data storage, and data access.
Data Standards and Policies:
- Establish, enforce, and maintain data standards, naming conventions, business glossaries, data and report catalogs and data management best practices.
- Develop and maintain data policies and procedures to ensure compliance with regulatory requirements.
Data Modeling and Design:
- Design and create conceptual, logical, and physical data models that meet business requirements and support efficient data management.
- Collaborate with business stakeholders, data scientists, and developers to understand data needs and design appropriate data structures.
Data Integration and Management:
- Define data integration strategies and ensure seamless data flow across systems and applications.
- Implement data governance practices, including data quality, data lineage, and data security.
Data Storage and Infrastructure:
- Optimize data storage and retrieval mechanisms for performance, scalability, and reliability.
- Collaboration and Leadership:
- Collaborate with cross-functional teams, including developers, business analysts, and project managers, to drive successful data-related initiatives.
- Provide technical guidance and mentorship to junior data team members.
