Data Architect

Data Architect, Financial Services Our client, a leading financial services organization in Abu Dhabi, are seeking an experienced Data Architect to join their AI function, working on large-scale, enterprise data platforms. This role offers the opportunity to design and build robust data architectures and pipelines that support both operational and advanced analytical use cases in a complex, fast-moving environment. The Role: You will be responsible for designing, implementing, and maintaining scalable ETL/ELT pipelines that ingest, cleanse, and transform data from a wide range of sources. Working with complex, high-volume datasets, you will ensure data is reliable, accessible, and optimised for business and analytical needs. You will collaborate closely with software engineering and AI/ML teams, applying best practices across data governance, security, and quality. A key part of the role involves continuously improving data pipelines, proactively identifying issues, and documenting data architectures, lineage, and metadata to support transparency and long-term scalability. Requirements: • 5+ years’ experience in data engineering, and/or data architecture. • Significant and proven experience of working on Databricks (or similar), and building AI use cases using these technologies • Proven experience building and operating automated data pipelines using modern orchestration and transformation tools, such as Airflow, Luigi and dbt. • Strong understanding of big data architectures and pipeline performance optimisation • Advanced SQL skills for data manipulation and querying • Proficiency in Python and at least one additional programming language (e.g. Scala or Java) • Hands-on experience with cloud-based data platforms • Strong analytical and problem-solving skills, with the ability to communicate complex technical concepts clearly • Bachelor’s degree in Computer Science, Engineering, or a related discipline If you feel that you fit the brief, please apply today!

Design, implement, and maintain scalable ETL/ELT pipelines that ingest, cleanse, and transform data from a wide range of sources. Ensure data is reliable, accessible, and optimised for operational and analytical needs. Collaborate with software engineering and AI/ML teams, applying data governance, security, and quality best practices. Continuously improve data pipelines, proactively identify issues, and document data architectures, lineage, and metadata to support transparency and long-term scalability.