Data Architect

- Data Modeling & Design: Design and develop logical and physical data models, including database schemas, blueprints, and architecture diagrams. - Data Architecture: Define scalable data architecture frameworks covering data collection, storage, processing, integration, and consumption. - Infrastructure Planning: Design and implement data warehouses, data lakes, ETL/ELT pipelines, and data integration solutions. - Security & Compliance: Ensure data platforms comply with regulatory and organizational standards such as GDPR, HIPAA, and other data privacy requirements. - Performance Optimization: Monitor, analyze, and optimize database and data platform performance to efficiently handle large-scale data volumes. - Data Governance: Establish standards for data quality, security, metadata management, accessibility, and lifecycle management. - Technology Strategy: Evaluate data technologies and recommend scalable, cost-effective solutions aligned with enterprise requirements. - Strategic Collaboration: Work closely with business stakeholders, data engineers, developers, and technical teams to align data architecture with business objectives. - Architecture Documentation: Create and maintain architecture diagrams, technical specifications, data models, and design documentation. - Problem Solving: Identify data architecture challenges and implement robust solutions to improve reliability, scalability, and maintainability. Essential Skills - Data Architecture & Modeling: Strong expertise in data modeling, database architecture, logical and physical data models, and schema design. - Database Technologies: Hands-on experience with SQL and relational database management systems (RDBMS). - Data Warehousing: Strong knowledge of modern data warehouse technologies such as Snowflake, Amazon Redshift , or equivalent platforms. - ETL/ELT: Experience designing and implementing ETL/ELT processes and enterprise data pipelines. - Cloud Data Platforms: Understanding of cloud-based data architecture and data services across AWS, Azure, or GCP. - Data Integration: Strong understanding of data integration patterns, APIs, batch processing, and real-time data processing. - Security & Compliance: Knowledge of data security, privacy, access controls, encryption, and compliance frameworks. - Performance Tuning: Ability to identify and resolve database and data pipeline performance bottlenecks. - Analytical & Strategic Thinking: Ability to understand business requirements and translate them into scalable technical and architectural solutions. - Communication Skills: Strong verbal and written communication skills, with the ability to explain complex architectural concepts to both technical and non-technical stakeholders. - Architecture Tools: Experience with data modeling and architecture tools such as ER/architecture diagramming tools.