Senior Data Engineer

We are seeking a highly experienced Senior Data Engineer to lead the technical design, implementation, and delivery of an enterprise-grade, AI‑ready Data Lakehouse platform. The ideal candidate will have strong software engineering experience with a focus on data pipeline development, data architecture, and scalable distributed systems. You will play a key role in designing and maintaining robust data infrastructure that enables advanced analytics and AI capabilities.

• Design and deploy a unified Data Lakehouse utilizing the Medallion architecture (Bronze, Silver, Gold) and open table formats such as Delta Lake and Apache Iceberg on cloud infrastructure hosted within Saudi Arabia.
• Build reusable automated ingestion frameworks (batch and streaming) capable of processing structured data (RDBMS, APIs) and unstructured data (PDFs, policy documents) to feed downstream AI models and semantic reasoning engines.
• Implement automated data quality circuit breakers, completeness, uniqueness, referential integrity checks, and end‑to‑end data lineage tracking frameworks.
• Optimize data processing workflows for performance, scalability, and cost‑efficiency.
• Monitor and maintain data systems, respond to SEVs or other urgent issues to ensure continuous operations.
• Ensure the platform adheres strictly to NCA National Cybersecurity Authority and NDMO National Data Management Office standards; implement AES‑256 encryption at rest, TLS
  1.2 in transit, robust Key Management Systems, and centralized audit logging.
• Design and deploy granular Role‑Based Access Control (RBAC) and Attribute‑Based Access Control (ABAC) integrating seamlessly with existing enterprise Identity Providers such as Active Directory.
• Lead hands‑on knowledge transfer sessions, pair‑programming with client engineers, creating operational runbooks, and conducting Game Day failure simulations to ensure the client’s team is fully ready to operate the platform independently.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

• 5years of proven experience in Data Engineering, Distributed Systems, or Big Data Architecture, with at least 2years specifically leading Data Lakehouse or Cloud Data Platform implementations.

• Programming
  
  Languages:
  
  proficiency in Python, Java, or Scala.
• Data Architecture & System Design: strong expertise in designing data‑intensive applications, complex data modeling, and schema design for enterprise environments.
• Distributed Systems & Lakehouse Technologies: deep hands‑on experience with distributed processing engines such as Apache Spark, Kafka, Hadoop, and open‑table formats such as Delta Lake, Apache Iceberg, and Apache Hudi.
• ETL / ELT & Orchestration: experience designing and building robust data pipelines using transformation and orchestration tools such as Apache Airflow, Prefect, or dbt.
• Database Ecosystems: proven track record with relational databases such as Postgre
  
  SQL, MySQL;
  No
  
  SQL platforms such as Mongo
  
  DB, Cassandra; and distributed SQL engines like Hive and Trino.
• Cloud Infrastructure: proven experience deploying enterprise data solutions on major cloud providers within localized Saudi cloud regions; expertise in Oracle Cloud Infrastructure (OCI) or Google Cloud Platform (GCP) is highly preferred, though experience with AWS or Azure is acceptable.
• AI & Data Science Enablement: prior experience building data pipelines optimized for Machine Learning, Natural Language Processing (NLP), vector embeddings, or Knowledge Graphs/ontologies is highly desirable.
• Security & Networking: strong understanding of enterprise network security, private endpoints, identity & access management (IAM), and cryptographic key management.

• Analytical
  
  Skills:
  
  strong problem‑solving skills with a keen eye for detail and a passion for data.
• Communication: excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non‑technical stakeholders.
• Leadership: demonstrated ability to lead technical teams, manage stakeholder expectations, and transition complex systems to internal IT Data teams.
• Regulatory Knowledge: familiarity with Saudi Arabian data compliance frameworks, NCA, CCC, NDMO, SDAIA is highly preferred.