Data Architect

Designs and manages the organization's data infrastructure, including databases, data warehouses, data lakes, and other data systems. Responsible for creating a blueprint or framework that defines how data is stored, organized, integrated, and accessed across the organization.

Roles and Responsibilities

• Data Modeling - Developing and designing data models that define how data will be stored, processed, and accessed. This includes creating conceptual, logical, and physical models representing the data's structure and relationships.
• Data Integration and Documentation - Designing solutions to integrate data from various sources within the organization and creating the necessary documentation. This involves ensuring that data from different systems can be combined and used cohesively.
• Data Security - Implementing data classification with stakeholders to safeguard sensitive data from unauthorized access, ensuring data privacy, and compliance with relevant regulations.
• Data Governance – Helps establish data governance frameworks and standards to ensure data quality, consistency, and compliance with data-related policies and regulations. Co-develops guidelines for master and metadata management and these are integrated in the organization's data architecture.
• Collaboration - working closely with other stakeholders, such as business analysts, data scientists, and developers, data architects help align data architecture with the organization's overall objectives.
• Data Migration - helps in planning and overseeing data migration processes when transitioning to new data systems or platforms. Crafting comprehensive data migration plans that encompass mapping data between the source and target systems, validating data quality, ensuring its integrity, and overseeing the safe and accurate transfer of data.

Job Requirements Technical Skills Ability to create conceptual, logical, and physical data models.
Proficiency in SQL and familiarity with database management systems like MySQL, Oracle, and SQL Server.
Understanding of data warehouse concepts, structures, and best practices especially dimensional modeling.
Knowledge of ETL processes and tools like Airflow and dbt. Good to have: Designing and implementing ETL processes and workflows.
Working knowledge of big data technologies like Hadoop, Spark, and others.
Experience with data storage solutions Cassandra, and MongoDB
Implementing and maintaining data warehousing solutions.
Familiarity with cloud platforms and services like AWS, Azure, or Google Cloud.
Ensuring data security, privacy, and compliance with relevant regulations. Soft Skills Creating clear and comprehensive documentation related to data architectures, systems, and processes.
Effectively communicating complex data concepts to non-technical stakeholders.
Collaborating with various departments and IT teams to align data strategies with organizational needs.
Comprehending and translating the company's goals and strategies into data architecture
Ability to develop and implement strategies related to data acquisition, storage, and usage to support business objectives.