Data Architecht

Data Architecht

Requirements

• 7-10 years of progressive experience as a Data Architect or in a similar senior data role with a focus on designing and managing complex database schemas and architectures.
• Extensive experience in designing and implementing data solutions for high-volume and high-throughput environments.
• Deep expertise in various database technologies, including specifically Snowflake, MySQL, and Cassandra.
• Deep expertise in various database technologies (e.g., Relational, NoSQL, Data Warehousing, Data Lakes) and their respective strengths and weaknesses for different use cases.
• Strong proficiency in data modeling techniques (e.g., Dimensional Modeling, ER Modeling) and data normalization/denormalization strategies.
• Experience with cloud-based data platforms and services (e.g., GCP, or AWS) and their scaling capabilities.
• Solid understanding of data governance, data security, and compliance principles.
• Excellent analytical and problem-solving skills with the ability to tackle complex architectural challenges.
• Strong communication and interpersonal skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences.
• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field, or equivalent practical experience.

Responsibilities

• Review and critically assess existing complex database schemas and data architectures for performance, scalability, security, and cost-effectiveness, especially in the context of high-volume data.
• Design and define next-generation data models (conceptual, logical, and physical) that are optimized for efficient storage, retrieval, and processing of large datasets.
• Develop and evolve data architecture strategies and roadmaps that align with business objectives and anticipate future data growth and analytical requirements.
• Architect and oversee the implementation of scalable and resilient database solutions capable of handling high transaction volumes and large-scale data processing.
• Evaluate and recommend new database technologies, data modeling techniques, and architectural patterns to improve our data platform’s capabilities and performance.
• Define and implement data governance, security, and compliance standards within the data architecture.
• Collaborate closely with data engineers, software engineers, data scientists, and business stakeholders to translate business requirements into technical data solutions.
• Explore and apply AI technologies and tools to enhance the data architecture process, such as using machine learning for schema optimization, anomaly detection in data pipelines, or automating data model generation and validation.
• Provide technical leadership and mentorship on data architecture best practices and principles.
• Troubleshoot and resolve complex data-related issues impacting performance and scalability.

Preferred Qualifications

• Experience in applying Artificial Intelligence or Machine Learning techniques to data architecture, data modeling, or database optimization tasks.
• Familiarity with MLOps principles and how data architecture supports the ML lifecycle.
• Experience with big data technologies such as Hadoop, Spark, Kafka, etc.
• Knowledge of data streaming and real-time data processing architectures.
• Experience with data cataloging, metadata management, and data lineage tools.