Key Responsibilities: 1. Data Analysis: Analyzing structured and unstructured data to derive actionable insights is crucial for informed decision-making and strategic planning. This ensures that the organization can leverage data to drive business outcomes and improve operational efficiency. 2. Data Architecture Design: Collaborating with the Data Engineering team to design and implement data models, pipelines, and storage solutions is essential for creating a robust data infrastructure. Defining and maintaining data architecture standards and best practices ensures consistency and reliability across data systems. Optimizing data systems for performance, scalability, and security is vital to handle growing data volumes and ensure data integrity and protection. 3. Collaboration and Stakeholder Engagement: Working with business units to understand their data needs and align them with architectural solutions ensures that data initiatives are aligned with business goals. Acting as a liaison between technical teams and business users facilitates effective communication and collaboration, ensuring that data solutions meet user requirements. 4. Data Governance and Quality: Implementing data governance practices to ensure data accuracy, consistency, and security is critical for maintaining high data quality standards. Proactively identifying and addressing data quality issues helps prevent data-related problems and ensures reliable data for analysis and reporting. Qualifications - External 1. Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or a related field provides the foundational knowledge required for the role. 2. Experience: 6+ years as a Data Analyst, Data Architect, or similar role ensures that the candidate has the necessary experience to handle complex data tasks and responsibilities. Hands-on experience with data modeling, architecture design, and analytics tools is essential for designing effective data solutions. Proficiency in SQL and data visualization tools enables the candidate to manage and present data effectively. Experience with cloud platforms (e.g., AWS, Azure) is crucial for leveraging modern data infrastructure and services. Familiarity with data warehouse solutions (e.g., Redshift, Snowflake) ensures the candidate can design and manage scalable data storage solutions. Understanding of data governance frameworks and tools is necessary for implementing effective data governance practice Show more Show less

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