Job description

The Senior Consultant role is positioned in Dubai, United Arab Emirates, and focuses on data analytics and data engineering responsibilities within enterprise data environments. The role centers on acting as a data analyst responsible for understanding detailed business requirements and translating them into data mapping and analysis artifacts that define end-to-end data flows from raw source systems to customized data marts, dashboards, and APIs for downstream data consumption. The position plays a critical role in the data management lifecycle, ensuring that data is systematically collected, transformed, governed, and made accessible for analytical and reporting purposes to enable informed decision-making and insight generation from large-scale datasets. The role requires active participation in Business Discovery Sessions to understand project and business requirements, collaboration with internal system support teams, database administrators, and MIS teams, and translation of existing requirements into target-state data marts and reports. The consultant prepares comprehensive data mapping documentation supporting the development of multiple data platform layers, including raw (bronze), enterprise data model (silver), and project-specific (gold) layers. The role provides ongoing support across multiple project phases, working closely with data engineers, data modelers, QA testers, and Power BI developers. The technical environment includes strong data querying and processing using SQL, SAS, Oracle, Apache Spark, and similar technologies, as well as data visualization tools such as Power BI, Business Objects, and Crystal Reports. The role demands deep expertise in distributed data processing frameworks, particularly Apache Spark, cloud platforms such as Azure and AWS including object storage, compute, networking, and data integration services, and strong knowledge of data warehousing, ETL concepts, data modeling, schema design, partitioning, and performance tuning. The position also requires experience handling structured and semi-structured data formats including JSON, Parquet, Avro, and XML, as well as knowledge of data governance, data quality assurance, compliance best practices, and core computer science fundamentals relevant to performance-critical data engineering.