Data Architect

Requirements
Design and implement data models: Develop conceptual, logical, and physical data models that meet business requirements.
Develop data warehousing strategies: Design and implement data warehouses and data lakes to support business intelligence and analytics.
Establish data governance policies: Define and enforce data quality standards, access controls, and security protocols.
Collaborate with stakeholders: Work with data scientists, engineers, and business analysts to understand data needs and translate them into technical solutions.
Evaluate and select data management tools: Research and recommend appropriate data management technologies and tools.
Oversee data migration and integration: Manage the process of migrating data from legacy systems to new platforms.
Performance tuning and optimization: Monitor and optimize data infrastructure performance to ensure efficient data access.
Stay up-to-date with industry trends: Keep abreast of the latest developments in data management technologies and best practices.
Skills
Data modeling: Expertise in various data modeling techniques, including relational, dimensional, and NoSQL.
Data warehousing: Strong understanding of data warehousing concepts and experience with data warehouse design and implementation.
ETL processes: Proficiency in designing and implementing Extract, Transform, Load (ETL) processes.
Database management systems (DBMS): Extensive knowledge of various DBMS platforms, such as SQL Server, Oracle, and MySQL.
Big data technologies: Familiarity with big data technologies like Hadoop, Spark, and NoSQL databases.
Business Intelligence: Experience with various BI tools and technologies including Tableau, PowerBI, Microstrategy, etc.,
Data governance: Understanding of data governance principles and best practices.
Cloud computing: Experience with cloud-based data platforms like AWS, Azure, and GCP.
Communication and collaboration: Excellent communication and interpersonal skills to effectively collaborate with stakeholders