Senior Data Architect

Senior Data Architect Lead the design and implementation of robust, scalable, and secure data architectures.
Develop and maintain enterprise-wide data models, ensuring alignment with business objectives.
Define and enforce data architecture standards, best practices, and governance policies.
Collaborate with stakeholders to understand data requirements and translate them into technical solutions.
Oversee data integration efforts, including ETL/ELT processes, data pipelines, and data warehousing.
Optimize data storage and retrieval methods for performance, scalability, and cost-effectiveness.
Evaluate and select appropriate technologies and platforms to support current and future data needs.
Conduct regular audits and reviews to ensure data integrity, security, and compliance.
Mentor and guide junior team members in data architecture principles and methodologies.
Stay updated on emerging data technologies and trends, driving innovation within the organization.Personal SkillsData Architecture and Modeling:
In-depth knowledge of data modeling (conceptual, logical, physical), and experience defining scalable and efficient architectures.Database Technologies:
Strong expertise in relational and NoSQL databases (e.g., Oracle, SQL Server, PostgreSQL, MongoDB, Cassandra).Big Data and Cloud Platforms:
Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP) for data storage and processing.ETL/ELT and Data Integration:
Proficiency in ETL/ELT tools and techniques for integrating, transforming, and migrating data across environments.Data Governance and Security:
Understanding of data governance frameworks, data quality principles, privacy regulations (GDPR, CCPA), and best practices for securing data.Performance Optimization:
Skills in tuning data systems, improving query performance, and designing data structures that scale.Enterprise Architecture Alignment:
Ability to align data architectures with broader enterprise architecture goals and business strategies.Analytical and Problem-Solving:
Strong analytical skills for diagnosing architectural issues, evaluating solutions, and implementing improvements.Communication and Collaboration:
Excellent communication abilities to work with cross-functional teams, gather requirements, and present complex architectures to stakeholders.Continuous Learning:
Commitment to staying updated with emerging data technologies, industry trends, and architectural best practices.Technical SkillsData Modeling:
Expertise in conceptual, logical, and physical data modeling, including entity-relationship design and dimensional modeling.Database Technologies:
Proficiency with relational (e.g., Oracle, SQL Server, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).Cloud and Big Data:
Experience with cloud-based data platforms (AWS, Azure, GCP) and big data technologies (Hadoop, Spark, Hive).ETL/ELT Tools:
Proficiency in ETL/ELT tools (e.g., Informatica, Talend, AWS Glue) and frameworks for data ingestion, transformation, and integration.Data Warehousing Solutions:
Hands-on experience with data warehousing platforms like Snowflake, Redshift, or BigQuery.Data Integration and Streaming:
Knowledge of data integration patterns, APIs, and streaming technologies (e.g., Kafka, Kinesis).Performance Optimization:
Ability to optimize database schemas, queries, and data pipelines for scalability, reliability, and speed.Data Security and Governance:
Familiarity with data governance frameworks, encryption, security controls, and compliance standards (GDPR, CCPA).Metadata Management and Cataloging:
Experience with metadata repositories, data catalogs, and lineage tracking tools.Infrastructure as Code and Automation:
Skill in using Infrastructure as Code (IaC) tools (e.g., Terraform, CloudFormation) and CI/CD pipelines for automated deployments and updates.Job Location:
Riyadh, Saudi ArabiaJob Role:
EngineeringYears of Experience:
Min:
11 Max:
20
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