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About the Role The Senior Data Architect is responsible for designing data platforms and lakehouses for customers and achieving optimal performance and stability of workloads running on Cloudera. This role serves as the technical authority for Cloudera engagements, encompassing presales and sizing through delivery and optimization, within the Data & AI business unit, specifically the Data Engineering & Management stream. Working collaboratively with customer architects, stakeholders, delivery teams, platform administrators, and Cloudera, the Senior Data Architect provides architectural direction, platform sizing, workload optimization, and technical leadership. Additionally, this position is tasked with building the practice by mentoring engineers and administrators and creating reference architectures, tuning playbooks, and sizing tools. The position is at a Senior / Lead level with a flexible location that is not limited to KSA. Responsibilities Data Architecture - Design end-to-end data architectures covering ingestion, storage, processing, serving, and governance layers for analytics and AI use cases. - Define data models, lakehouse layering, table formats, and data lifecycle and retention strategies. - Make sound technology choices and trade-offs, including batch vs streaming, lake vs warehouse, and on-prem vs hybrid. - Set architecture standards, patterns, and data contracts that delivery teams follow. Cloudera Platform & Workload Optimisation - Architect and size Cloudera Data Platform environments (CDP Private Cloud Base and Data Services), including topology, capacity, and HA. - Diagnose and optimise workloads on Cloudera, including Spark, Hive, and Impala query tuning, YARN resource management and queueing, file layout, partitioning and compaction, and contention under mixed workloads. - Make ingestion and processing pipelines more stable and faster, while controlling latency and SLAs. - Plan capacity and growth, and determine when to tune, re-architect, or scale out. - Guide platform security and governance design (Kerberos, Ranger, Atlas) with the admin team. - Provide technical direction on upgrades and migrations. Presales & Customer Leadership - Write the architecture and Cloudera sections of proposals, size licenses and infrastructure, and estimate effort. - Conduct platform health checks and performance assessments as part of client engagements. - Present to customer architects and stakeholders, serving as the technical counterpart to Cloudera. Practice Building - Mentor engineers and administrators. - Develop reference architectures, tuning playbooks, and sizing tools. Success in the First 12 Months - Act as the named architect on all active Cloudera engagements. - Deliver measurable workload performance improvements for at least one customer platform. - Publish a Cloudera reference architecture, a tuning playbook, and a sizing toolkit for bids. Our Culture & Code of Conduct We take pride in a culture based on collaboration, innovation, and uncompromising integrity. We seek individuals who share these values and are committed to customer-centricity and ethical excellence. All employees are expected to uphold our Code of Conduct, which acts as a guiding framework for responsible behavior in all our interactions — from collaboration among team members to engagements with clients and partners globally. Requirements - 10+ years of experience in data engineering and data architecture, with a track record of designing enterprise data platforms. - Strong hands-on Cloudera experience (CDH and/or CDP) in production, with proven results in tuning and optimizing workloads. - Deep knowledge of distributed processing and query engines (Spark, Hive, Impala) and of resource management (YARN). - Solid data modeling and lakehouse or warehouse design fundamentals. - Experience with both batch and streaming ingestion (e.g., Kafka, NiFi, CDC). - Ability to lead technically and explain trade-offs to customers. - Experience with open table formats (Iceberg) and federated query engines (e.g., Trino) is an advantage. - Exposure to other data platforms (cloud data platforms, enterprise warehouses), to position Cloudera objectively, is an advantage. - Experience designing data platforms for AI/ML consumption is also an advantage. - Professional level of English; Arabic is an advantage. - Cloudera certifications preferred.
