Data Architecture Specialist

Role Summary: The specialist, Data Architecture plays a crucial role in designing, implementing, and optimizing data architecture solutions to meet the organization's data management needs. This role involves developing data models, defining data standards, and ensuring data integrity and security across the enterprise business goals.

Job Duties & Responsibilities:

• Develop and maintain data architecture frameworks, standards, and policies to guide data management practices.
• Design and implement data models, databases, and data warehouses to support business requirements and analytics initiatives.
• Collaborate with business stakeholders to understand data requirements and translate them into technical solutions.
• Define data governance processes and controls to ensure data quality, consistency, and compliance with regulatory requirements.
• Evaluate and select data management tools and technologies to support data integration, storage, and retrieval needs.
• Conduct data analysis and profiling to identify data quality issues, anomalies, and opportunities for improvement.
• Provide technical guidance and support to project teams and stakeholders on data architecture best practices and methodologies.
• Stay updated on emerging trends and technologies in data management and recommend innovative solutions to enhance data architecture capabilities.

Education & Experience:

• Bachelor’s degree in computer science, Information Technology, or a related field.
• Minimum of 4 years of progressive experience in data architecture, database design, and data modeling roles.
• Deep knowledge in data modeling tools and techniques, such as ER diagrams, dimensional modeling, and data flow diagrams.

Skills:

• Excellent analytical and problem-solving skills, with the ability to analyze complex data sets and derive actionable insights.
• Excellent in designing conceptual, logical, and physical data models using tools such as ERwin, ER/Studio, or PowerDesigner.
• Ability to translate business requirements into data models that accurately represent the organization's data assets.
• Strong understanding of database design principles, normalization techniques, integration tools and indexing strategies.
• Experience with relational database management systems (RDBMS) and familiarity with schema design for performance and scalability.
• Familiarity with cloud-based data services and platforms, such as Amazon Redshift, Google BigQuery, or Azure SQL Database.
• Experience with cloud data migration, storage, and analytics solutions.
• Knowledge of data governance frameworks, policies, and procedures.
• Ability to establish data processes for managing data assets, defining data ownership, and ensuring data quality, integrity, and security.
• Understanding of data quality dimensions, metrics, and methodologies. Ability to implement data quality rules, validation checks, and cleansing processes to improve data accuracy, completeness, and consistency.
• Strong analytical and problem-solving skills, with the ability to analyze complex data sets, identify patterns, trends, and anomalies, and derive actionable insights to support business decision-making.
• Excellent verbal and written communication skills, with the ability to effectively communicate technical concepts to non-technical stakeholders.
• Experience in preparing technical documentation, data dictionaries, and architectural diagrams.
• Ability to collaborate effectively with cross-functional teams, including business stakeholders, data engineers, data analysts, developers, and IT infrastructure teams.
• Experience in facilitating workshops, meetings, and discussions to gather requirements and drive consensus.