Data Architect

Data Architect Description Entrada AI, Inc. is seeking an experienced Databricks Data Architect to join our growing team of consultants to lead the design and implementation of our client’s data architecture and strategy. In this role, you will be responsible for defining how data will be stored, consumed, integrated, and managed across the client organization. You will work closely with data engineers, analysts, and business stakeholders to ensure that our data systems are scalable, secure, and aligned with business goals. Key Responsibilities Design and oversee the development of the overall data architecture, including databases, data warehouses, data lakes, and integration systems. Collaborate with stakeholders to understand business requirements and translate them into data architecture solutions that support current and future needs. Define and implement data management processes, including data modeling, metadata management, data quality, and data governance. Ensure data security and compliance with relevant regulations by designing and implementing appropriate access controls and data protection mechanisms. Optimize data architectures for performance, scalability, and cost-efficiency in both on-premise and cloud environments. Provide guidance and best practices to data engineers, analysts, and developers on data architecture and design. Stay up-to-date with the latest trends and technologies in data architecture, and apply them to enhance our data infrastructure. Create and maintain documentation for data architecture, including data flow diagrams, data models, and system integrations. Travel to client sites as needed (up to 20% travel required) Qualifications Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related field. 7+ years of experience in data architecture, data engineering, or related fields. 4+ years of experience with Databricks Strong understanding of data management principles, including data modeling, ETL processes, data integration, and data warehousing. Experience with relational and NoSQL databases, data lakes, and big data technologies (e.g., Hadoop, Spark, Kafka). Proficiency in data modeling tools and techniques, and familiarity with data governance and data quality frameworks. Experience with cloud platforms (AWS, GCP, Azure) and modern data architectures, including serverless and microservices. Strong problem-solving and analytical skills, with the ability to design and implement complex data systems. Excellent communication and leadership skills, with the ability to work effectively across teams and influence stakeholders.