We are seeking a Data Engineer with strong AWS and banking sector experience to join our core engineering squad in the UAE.

In this role, you will design, construct, and optimize scalable Lakehouse data solutions that power enterprise analytics and advanced machine learning models. Operating at the intersection of big data, cloud architecture, and MLOps, you will unify data warehousing and data lake capabilities to process complex, high-volume financial data while maintaining strict banking security, ACID compliance, and data governance standards.

What You'll Do....

• Build Next-Gen Lakehouse Architectures: Design, build, and optimize scalable data solutions using Lakehouse architectures (Databricks, Delta Lake) to unify data warehousing and data lake capabilities on AWS
• Develop High-Throughput Pipelines: Build robust batch and real-time ETL/ELT pipelines using PySpark, Apache Kafka, and SQL to ingest and transform complex financial datasets from core banking, market data, and transactional systems
• Optimize for Scale & FinOps: Maximize query performance and storage efficiency across AWS services (S3, Redshift, EMR, Athena, Glue) using advanced partitioning, indexing, and parallel processing to drive down latency and cloud compute costs
• Support Machine Learning & MLOps: Partner with Data Scientists and MLOps Engineers to build automated feature engineering pipelines, track experiments (MLflow), containerize workflows (Docker, EKS), and deploy models to production (AWS SageMaker)
• Enforce Banking-Grade Governance: Implement end-to-end data security, encryption, access controls, and audit trails to ensure 100% compliance with Central Bank data sovereignty and privacy mandates
• Automate Everything: Drive software engineering best practices by managing Infrastructure as Code (Terraform), authoring CI/CD pipelines (GitHub Actions/CodePipeline), and writing clean, well-tested Python code