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Key Responsibilities:
Data Architecture & Design
Key Responsibilities:
Data Architecture & Design
- Data Modeling: Design, maintain, and evolve comprehensive data models (Conceptual, Logical, and Physical) for core business services and platforms.
- Data Flow: Define and create data flow diagrams and orchestration strategies, ensuring efficient and governed data movement between up- and downstream systems.
- System Alignment: Collaborate closely with Application and Cloud Architects to ensure the organization s technical systems are designed to fully support the established data architecture standards.
- Technology Selection: Develop product short-lists and evaluation criteria for selecting data architecture components, such as data warehousing solutions, Big Data platforms (e.g., Hadoop, Spark, Kafka), and database technologies (SQL/NoSQL).
- Governance Frameworks: Evolve and define data governance policies, standards, and best practices across the organization.
- Metadata Management: Design, support, and manage data dictionaries, metadata repositories, and common entities to ensure consistent use and definition of data.
- Data Quality: Drive the standards for Data Quality across multiple datasets, ensuring consistency and data trust across the enterprise.
- Compliance: Design data retention, upgrade, management, decommission, and archive strategies in compliance with data policies and regulatory standards (e.g., data privacy).
- Oversight: Provide technical oversight, advice, and guidance to other Data Architects, Data Engineers, and development teams regarding data structures and associated components.
- Standard Enforcement: Ensure project teams adhere to the corporate data standards and architectural principles set by data leadership.
- Mentorship: Mentor and support colleagues in multi-disciplinary teams, promoting best practices in data architecture and design.
- Required Skills and Experience
- Advanced experience in designing and implementing data models (Star Schema, Snowflake, etc.).
- Expertise in a wide variety of database technologies, including relational (SQL) and NoSQL platforms, and Big Data technologies.
- Demonstrated ability to architect scalable, high-performance data warehousing and data lake solutions on major cloud platforms (e.g., AWS, Azure, Google Cloud Platform).
- Strong understanding of ETL/ELT tools, data integration strategies, and advanced data processing techniques.
- Communication: Excellent verbal and written communication skills with the ability to translate complex technical information and language into simple, accessible terms for non-technical stakeholders.
- Leadership: Strong leadership skills with the proven ability to establish relationships, manage differing stakeholder perspectives, and drive technical direction across teams.
- Strategic Thinking: A systematic, disciplined, and analytical approach to problem-solving, with an awareness of evolving business needs and technology capabilities.