Responsibilities:

• Collaborate with stakeholders to understand business requirements and translate them into data architecture designs and solutions.

• Design and develop data models, data dictionaries, and metadata repositories to ensure consistency, integrity, and usability of data assets.

• Define data standards, policies, and best practices for data management, governance, and quality assurance.

• Evaluate and recommend data technologies, platforms, and tools to support data integration, storage, processing, and analytics needs.

• Design and implement data pipelines and ETL (Extract, Transform, Load) processes to ingest, transform, and integrate data from various sources into data repositories.

• Develop and maintain data architecture documentation, including data flow diagrams, data lineage, and system interface specifications.

• Collaborate with cross-functional teams to implement data security and privacy controls, ensuring compliance with regulatory requirements (e.g., GDPR, CCPA).

• Provide technical leadership and guidance to IT teams and business stakeholders on data architecture and data management best practices.

• Stay up-to-date on emerging trends and technologies in data architecture, big data, cloud computing, and analytics to drive innovation and continuous improvement.

Qualifications:

• Bachelor's degree in Computer Science, Information Systems, or related field; advanced degree (e.g., Master's) preferred.

• Proven experience as a Data Architect or similar role, with a strong background in data modeling, database design, and data integration.

• Extensive knowledge of relational database management systems (e.g., SQL Server, Oracle, PostgreSQL) and data warehousing concepts and methodologies.

• Hands-on experience with data modeling tools (e.g., ERwin, ER/Studio, PowerDesigner) and database management systems.

• Proficiency in data manipulation languages (e.g., SQL, PL/SQL) and scripting languages (e.g., Python, R) for data analysis and automation.

• Experience with cloud-based data platforms (e.g., AWS, Azure, Google Cloud) and big data technologies (e.g., Hadoop, Spark) is a plus.

• Strong analytical, problem-solving, and communication skills, with the ability to work effectively in a team environment and interact with stakeholders at all levels.

• Excellent organizational skills and attention to detail, with a commitment to delivering high-quality solutions on time and within budget.