Role Overview
We are seeking a Senior Data Engineer Architect & Lead to design, build, and oversee our enterprise data architecture on Google Cloud Platform (GCP). In this leadership role, you will orchestrate complex data workflows, manage real-time data ingestion, and establish secure, highly scalable data pipelines.
You will lead the technical strategy for integrating legacy transactional systems with modern cloud infrastructure, leveraging Change Data Capture (CDC), serverless processing, and advanced BigQuery data warehousing patterns.
Key Responsibilities
Architecture & Technical Leadership
Lead the design and implementation of scalable data architectures on GCP. Drive technical decisions and establish best practices for data governance, code quality, and pipeline reliability.
Real-Time Data Ingestion (CDC)
Design and maintain Change Data Capture pipelines using Oracle Datastream and LogMiner to enable reliable, low-latency data replication into the cloud.
Data Processing
Develop and optimize distributed data processing pipelines using Python and PySpark on Serverless Dataproc.
Analytics Engineering
Build and manage SQL-based transformations and data models using Dataform (.sqlx).
Data Warehousing
Design and implement efficient BigQuery patterns, including partitioning, clustering, and incremental (merge-based) data loading for large-scale datasets.
Workflow Orchestration
Build and manage end-to-end pipelines using Cloud Composer (Apache Airflow) and DAG-based orchestration.
Security & Compliance
Implement data security practices including HMAC tokenization and PII masking to ensure secure data handling in transit and at rest.
Required Technical Skills
Database & CDC
Strong experience with Oracle databases and CDC tools (Datastream, LogMiner) for high-throughput replication.
Cloud & Processing
Advanced proficiency in Python and PySpark with hands-on experience in GCP Serverless Dataproc.
Data Warehousing
Expertise in BigQuery including schema design, partitioning, clustering, and incremental loading strategies.
Transformation & Orchestration
Experience with Dataform and Cloud Composer (Airflow) for building production-grade data pipelines.
Security
Understanding of cryptographic techniques, especially HMAC tokenization and PII protection strategies.
Qualifications & Experience
- Minimum 5+ years of experience in Data Engineering and Cloud Architecture
- Strong hands-on experience with Google Cloud Platform (GCP)
- Advanced proficiency in Python and SQL
- Proven experience leading data architecture initiatives and enterprise-scale systems design
- Ability to translate complex requirements into scalable, production-ready data systems
📍 Jeddah, KSA
