Role overview

A Data Architect is a professional responsible for designing, creating, and managing an organization's data architecture. They play a critical role in developing data strategies, defining data standards, and implementing data management solutions to ensure the efficient and effective use of data across the organization. Data Architects collaborate with various stakeholders to understand business requirements, design data models, and establish data governance frameworks.

Overall, a Data Architect plays a vital role in shaping an organization's data landscape, ensuring that data assets are effectively managed, governed, and leveraged to drive business value and innovation. They combine technical expertise with strategic vision to design scalable, flexible, and sustainable data architectures that meet the evolving needs of the organization.

Key Responsibilities

1. Data Strategy and Planning:

• Collaborate with business stakeholders to understand organizational goals and data requirements.
• Develop data strategies aligned with business objectives, regulatory requirements, and industry best practices.
• Define data architecture principles, standards, and guidelines to guide data management initiatives.

2. Data Modeling and Design:

• Design conceptual, logical, and physical data models to represent the structure and relationships of data.
• Identify data entities, attributes, and relationships based on business needs and use cases.
• Ensure data models adhere to normalization principles, data integrity constraints, and performance requirements.

3. Data Governance and Quality:

• Establish data governance policies, procedures, and controls to ensure data integrity, privacy, and security.
• Define data quality standards and metrics to measure and monitor data quality.
• Implement data governance frameworks to enforce compliance with regulatory requirements and internal policies.

4. Data Integration and Architecture:

• Design data integration solutions to facilitate the flow of data across systems and applications.
• Evaluate and select technologies for data integration, ETL (Extract, Transform, Load), and data migration.
• Define data architecture patterns and reference architectures to guide the implementation of data solutions.

5. Metadata Management:

• Develop metadata management strategies to catalog and classify data assets.
• Establish metadata standards and taxonomies to facilitate data discovery and lineage.
• Implement metadata repositories and tools to capture and maintain metadata across the data lifecycle.

6. Collaboration and Communication:

• Collaborate with cross-functional teams, including data engineers, developers, and business analysts.
• Communicate data architecture concepts, principles, and decisions to technical and non-technical stakeholders.
• Provide guidance and mentorship to junior team members on data architecture best practices.

Skills and Qualifications

• Proficiency in data modeling techniques and tools such as ERwin, ER/Studio, or PowerDesigner.
• Strong understanding of database technologies, data warehousing, and big data platforms.
• Knowledge of data governance frameworks, data quality management, and regulatory compliance (e.g., GDPR, CCPA).
• Experience with data integration technologies and ETL tools (e.g., Informatica, Talend, Apache NiFi).
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and data services (e.g., Amazon Redshift, Azure SQL Data Warehouse).
• Excellent analytical and problem-solving skills, with attention to detail.
• Effective communication and stakeholder management skills.
• Bachelor’s or master’s degree in computer science, information systems, or a related field. Professional certifications in data architecture (e.g., CDMP, DAMA) are a plus.