Senior Data Architect

Responsibilities

• Lead the design and implementation of robust, scalable, and secure data architectures.
• Develop and maintain enterprise-wide data models, ensuring alignment with business objectives.
• Define and enforce data architecture standards, best practices, and governance policies.
• Collaborate with stakeholders to understand data requirements and translate them into technical solutions.
• Oversee data integration efforts, including ETL/ELT processes, data pipelines, and data warehousing.
• Optimize data storage and retrieval methods for performance, scalability, and cost-effectiveness.
• Evaluate and select appropriate technologies and platforms to support current and future data needs.
• Conduct regular audits and reviews to ensure data integrity, security, and compliance.
• Mentor and guide junior team members in data architecture principles and methodologies.
• Stay updated on emerging data technologies and trends, driving innovation within the organization.

Skills

• Data Architecture and Modeling: In-depth knowledge of data modeling (conceptual, logical, physical), and experience defining scalable and efficient architectures.
• Database Technologies: Strong expertise in relational and NoSQL databases (e.g., Oracle, SQL Server, PostgreSQL, MongoDB, Cassandra).
• Big Data and Cloud Platforms: Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP) for data storage and processing.
• ETL/ELT and Data Integration: Proficiency in ETL/ELT tools and techniques for integrating, transforming, and migrating data across environments.
• Data Governance and Security: Understanding of data governance frameworks, data quality principles, privacy regulations (GDPR, CCPA), and best practices for securing data.
• Performance Optimization: Skills in tuning data systems, improving query performance, and designing data structures that scale.
• Enterprise Architecture Alignment: Ability to align data architectures with broader enterprise architecture goals and business strategies.
• Analytical and Problem-Solving: Strong analytical skills for diagnosing architectural issues, evaluating solutions, and implementing improvements.
• Communication and Collaboration: Excellent communication abilities to work with cross-functional teams, gather requirements, and present complex architectures to stakeholders.
• Continuous Learning: Commitment to staying updated with emerging data technologies, industry trends, and architectural best practices.