About
The company is an ADX-listed public company with Abu Dhabi-based G42 as its majority shareholder and is the region’s leading big data analytics company powered by GenAI. It combines big data, analytics, and AI expertise to create business and positive societal impact. The role of Senior Data Engineer blends strong data engineering with data architecture leadership and analytical curiosity, operating across a multicultural, multinational environment.
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Job Description
We are seeking a Senior Data Engineer to own end-to-end data delivery – from source-system analysis and data architecture through data modeling, pipeline engineering, and analytics enablement. You will define the target-state architecture, model enterprise data, engineer reliable end-to-end pipelines, and turn complex datasets into trusted, decision-ready insights.
Responsibilities
- Own the complete data lifecycle – requirements, sourcing, architecture, modeling, pipeline engineering, quality, and delivery of analytics-ready data.
- Translate business and information needs into delivery roadmaps, then design, build, and operate the solutions that meet them.
- Define the target-state data architecture, infrastructure, and interfaces to data sources, including tooling for automated data loads.
- Design lake/warehouse/lakehouse architecture spanning ingestion, storage, processing, serving, and consumption layers, embedding security, access control, privacy, and compliance considerations.
- Analyze source systems to understand data semantics and develop conceptual, logical, and physical data models, defining granularity and identifying facts and dimensions.
- Design, develop, and maintain scalable batch and real-time/streaming data pipelines that ingest from databases, applications, files, and event streams.
- Optimize data processing and distributed compute, tuning for performance, cost, and scalability.
- Apply software-engineering best practices – version control, code review, automated testing, and continuous integration and delivery for data assets.
- Build and maintain data visualizations and self-service reporting, detecting anomalies and validating quality to support confident, data-driven decisions.
Requirements
- Minimum 10 years of relevant experience across data engineering, data architecture, data modeling, and data analysis.
- Bachelor’s degree in Information Technology, Computer Science, or a related field.
- Proven experience with the Microsoft Azure data stack (e.g., Azure Data Factory, Azure Databricks/Synapse, ADLS Gen2, Azure SQL).
- Advanced data querying and manipulation skills, including complex logic, analytical functions, and performance tuning.
- Strong expertise defining granularity and identifying facts and dimensions for star and snowflake schemas based on business requirements.
- Excellent problem-solving and communication skills, with a customer-centric mindset.
- Collaborative team player who thrives in a multicultural, multinational environment.
