Data Architect

About the Role:We are seeking an experienced Data Architect with a strong background in designing and implementing scalable, high-performance data solutions in the cloud, with a preference for AWS. The ideal candidate will have extensive experience in architecting data lakes, data warehouses, and real-time analytics platforms. You will play a critical role in shaping our data strategy and building systems that enable advanced analytics and data-driven decision-making across the organization.

Key Responsibilities:

• Architect and Design: Develop and implement robust and scalable data architecture solutions in AWS to support business intelligence, analytics, and data science initiatives.
  
• Data Management: Define and maintain data architecture frameworks, standards, and principles, including modeling, metadata management, data security, and compliance.
  
• ETL/ELT Pipelines: Design, implement, and optimize data pipelines for efficient data ingestion and transformation using AWS services like Glue, Lambda, Step Functions, and EMR.
  
• Data Storage and Processing: Architect data lakes and warehouses using AWS technologies such as S3, Redshift, Athena, and DynamoDB, ensuring high performance and reliability.
  
• Data Governance: Establish data governance practices, ensuring compliance with data privacy regulations and security standards.
  
• Performance Tuning: Optimize queries, storage, and data processing performance while managing costs in a cloud environment.
  
• Collaboration: Work closely with data engineers, data scientists, and business analysts to understand data requirements and ensure seamless integration and accessibility.
  
• Innovation: Stay updated on emerging data architecture trends and AWS advancements to continuously improve our data platforms.
  

Required Skills and Qualifications:

• Experience: Minimum of 5+ years as a Data Architect or in a similar role, with extensive experience in AWS cloud services.
  
• Technical Expertise: Strong proficiency with AWS services, such as S3, Redshift, Glue, Kinesis, RDS, Lambda, IAM, and VPCs.
  
• Data Modeling: In-depth knowledge of data modeling, data integration, and data warehousing principles.
  
• Big Data Technologies: Familiarity with big data processing frameworks like Apache Spark or Hadoop.
  
• Database Experience: Hands-on experience with both relational (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., DynamoDB, MongoDB).
  
• Programming Skills: Proficient in SQL and one or more programming languages, such as Python, Java, or Scala.
  
• Data Security: Understanding of data security practices and compliance requirements (e.g., GDPR, CCPA, or regional regulations like Sadaya for Saudi Arabia).
  
• DevOps Practices: Knowledge of CI/CD, infrastructure as code (e.g., AWS CloudFormation, Terraform), and containerization technologies like Docker and Kubernetes.
  
• Analytical Skills: Strong analytical and problem-solving skills with a keen eye for detail.
  
• Communication: Excellent communication and documentation skills to articulate data strategies and solutions to both technical and non-technical stakeholders.