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.