Machine Learning Engineer jobs in United Arab Emirates

Where elite tech talent meets world‑class opportunities! At Xenon7, we work with leading enterprises and innovative startups on exciting, cutting‑edge projects that leverage the latest technologies across various domains of IT including Data, Web, Infrastructure, AI, and many others. Our expertise in IT solutions development and on‑demand resources allows us to partner with clients on transformative initiatives, driving innovation and business growth. Whether it's empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today's most complex challenges.

Join one of Egypt’s premier financial institutions, renowned for its extensive suite of banking services, including Institutional Banking and Personal Banking. With a global presence through over 50 branches and correspondents, we serve a diverse and dynamic clientele. As we embark on a groundbreaking digital transformation journey, we are committed to leveraging the latest technologies to establish a state‑of‑the‑art data architecture that will redefine our performance and service delivery.

We are seeking a highly experienced Senior Cloudera Machine Learning to lead and manage enterprise‑scale Hadoop/Cloudera environments. The ideal candidate will have strong hands‑on experience with Cloudera platforms, proven leadership managing teams of data engineers, and deep expertise in building and overseeing ETL pipelines. This role requires the ability to design, understand, and communicate complex data architectures and data flows.

• Platform & Cluster Management: Administer, maintain, and optimize Cloudera Hadoop clusters (CDP or legacy Cloudera distributions). Ensure high availability, performance tuning, capacity planning, and cluster security. Manage upgrades, patching, monitoring, and troubleshooting of Cloudera services (HDFS, YARN, Hive, HBase, Impala, Spark, Kafka, etc.).
• Data Engineering & ETL: Oversee the design, development, and maintenance of ETL/ELT pipelines using tools such as Spark, Hive, Kafka, Airflow, NiFi, or similar. Review and guide data ingestion, transformation, and storage strategies across batch and streaming workloads. Ensure data quality, reliability, and scalability of pipelines.
• Architecture & Design: Design, understand, and document data storage architectures and data flow diagrams. Collaborate with stakeholders to define end‑to‑end data platform architecture. Translate business requirements into scalable, secure data solutions.
• Leadership: Lead and mentor teams of data engineers, providing technical guidance and best practices. Set standards for development, deployment, monitoring, and documentation. Work closely with data scientists, analysts, DevOps, and application teams.
• Security & Governance: Implement security best practices including Kerberos, Ranger, and data access controls. Support data governance, lineage, and compliance requirements.

• Attractive, market‑leading salary package.
• Clear career advancement path with professional development opportunities.
• One‑year contract with Xenon7, presenting a significant opportunity for renewal.

• 7+ years of experience in data platforms, Hadoop, or big data administration.
• Deep experience with CML workspaces, projects, and runtimes.
• Strong hands‑on experience with Cloudera (CDH/CDP) administration.
• Proven experience managing and mentoring data engineering teams.
• Strong background in ETL pipeline design and implementation.
• Expertise with Spark, Hive, HDFS, YARN, Kafka, Airflow/NiFi (or similar tools).
• Ability to design and draw architecture diagrams for data storage and data flows.
• Solid understanding of Linux, networking, and distributed systems.
• Experience with cloud platforms (AWS, Azure, or GCP) is a strong plus.
• Excellent communication and documentation skills.
• Nice to have: Cloudera certification(s).
• Experience with containerization (Docker, Kubernetes).
• Exposure to data governance tools and metadata management.
• Experience in large‑scale enterprise or regulated environments.