Senior Data Engineer - Hybrid - KSA RTG

Robusta assists organizations in transitioning to a digital-first approach, crafting unforgettable experiences for their customers. We provide strategy, design, product, and technology services to prominent businesses and brands, utilizing our go-to-market expertise to facilitate seamless customer experiences and enhance conversion rates.

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
. This role is critical in building the foundational data layer for a large-scale digital transformation initiative that will support AI agents, digital workers, and knowledge graph (ontology) systems
.

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.

This position also involves technical leadership
, mentoring engineering teams in a collaborative co‑building model, and ensuring long‑term operational ownership.

• Lakehouse Architecture & Implementation: Design and deploy a unified Data Lakehouse utilizing the Medallion architecture (Bronze, Silver, Gold) and open table formats (e.g., Delta Lake, Apache Iceberg) on cloud infrastructure hosted within Saudi Arabia.
• Data Ingestion & Pipeline Engineering: Build reusable, automated ingestion frameworks (batch and streaming) capable of processing both structured data (RDBMS, APIs) and unstructured data (PDFs, policy documents) to feed downstream AI models and semantic reasoning engines.
• Data Quality & Governance: Implement automated data quality "circuit breakers" (completeness, uniqueness, referential integrity) and end‑to‑end data lineage tracking frameworks.
• Optimization: Optimize data processing workflows for performance, scalability, and cost‑efficiency.
• System Monitoring and Maintenance: Monitor and maintain data systems, responding to SEVs or other urgent issues to ensure continuous operations.
• Security & Compliance: 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 (KMS), and centralized audit logging.
• Access Control Integration: Design and deploy granular Role‑Based Access Control (RBAC) and Attribute‑Based Access Control (ABAC), integrating seamlessly with existing enterprise Identity Providers (e.g., Active Directory).
• Capability Building & Handover: 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.

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Experience: 5+ years of proven experience in Data Engineering, Distributed Systems, or Big Data Architecture, with at least 2+ years specifically leading Data Lakehouse or Cloud Data Platform implementations.

• Programming
  
  Languages:
  
  Proficiency in programming languages such as 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 (e.g., Apache Spark, Kafka, Hadoop) and modern open table formats (e.g., Delta Lake, Apache Iceberg, Apache Hudi).
• ETL/ELT & Orchestration: Experience designing and building robust data pipelines using modern transformation and orchestration tools (e.g., Apache Airflow, Prefect, dbt).
• Database Ecosystems: Proven track record with relational databases (e.g., Postgre
  
  SQL, MySQL), No
  
  SQL platforms (e.g., Mongo
  
  DB, Cassandra), and distributed SQL query engines like Hive and Trino.
• Cloud Infrastructure: Proven experience deploying…