Senior Data Architect – CVM & Marketing Analytics

This is a fully remote position, open to applicants in Egypt.

📋 Description

• Take full ownership of the comprehensive technical architecture for the data platform.

• Establish methods for data ingestion, storage, processing, transformation, serving, and governance.

• Create and enhance scalable architectures for both batch and streaming data.

• Define lakehouse architectures utilizing open table formats and suitable query engines.

• Design architectures for real-time data serving and OLAP workloads tailored for analytics.

• Set standards for data pipelines, schema evolution, data quality, lineage, and access control.

• Define architectural frameworks for ETL/ELT processes and data processing.

• Provide guidance on technologies like Spark, Kafka, Airflow, and SQL throughout the data platform.

• Develop data platforms that prioritize scalability, performance, cost-effectiveness, and multi-tenancy.

• Assess architectural trade-offs and effectively communicate technical decisions.

• Establish reusable architecture patterns and engineering standards across data teams.

• Support the architecture for multiple deployments of the same data platform for various clients.

• Contribute to the development of data mesh and data product operating models as appropriate.

• Collaborate closely with data engineers and technical stakeholders to ensure consistent implementation of architectural standards.

• Identify architectural constraints and spearhead enhancements in reliability, scalability, and data processing efficiency.

• Define technical strategies for schema management, data governance, and data lifecycle management.

• Design architectures that are suitable for both self-managed and on-premises infrastructure environments.

⛳️ Requirements

• Proven experience as a Data Architect, Technical Data Architect, or in a similar senior data architecture position.

• Demonstrated responsibility for data platform architecture, beyond just pipeline development and delivery.

• Strong practical experience with both batch and streaming data processing.

• In-depth knowledge of data architecture, ETL/ELT processes, data warehousing, and lakehouse design.

• Hands-on experience with Apache Spark, Kafka, Airflow, and advanced SQL.

• Experience in designing lakehouse architectures, open table formats, and integrating query engines.

• Experience in creating real-time data serving architectures and OLAP data stores.

• Strong grasp of data modeling, schema design, and schema evolution.

• Proven experience in establishing standards for data quality, lineage, governance, and access control.

• Experience in designing and managing self-hosted or on-premises data infrastructure.

• Strong understanding of distributed data processing and scalable data platforms.

• Experience in crafting multi-tenant data architectures with an understanding of the related isolation and performance trade-offs.

• Ability to assess architectural decisions based on scalability, performance, reliability, operational complexity, and cost.

• Experience in supporting multiple client deployments of the same data platform is highly preferred.

• Familiarity with data mesh and data product operating models.

• Strong understanding of data lifecycle management and platform reliability.

• Ability to establish technical standards and architecture guidelines for data engineering teams.

• Excellent communication skills with the ability to articulate complex architectural decisions and trade-offs to technical stakeholders.

• Experience working closely with data engineers, platform engineers, and other technical teams.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and the option for remote work.

• Opportunities for professional development and continuing education.

• A collaborative and innovative work environment.