Senior Data Engineer
Indexed description
Roles & Responsibilities
Data Source Analysis:
- Analyze multiple structured and unstructured data sources to understand schemas, data quality, and relationships
- Assess and document the metadata, formats, and business rules of incoming data sets
- Perform comprehensive data profiling to assess completeness, accuracy, uniqueness, and consistency of data
- Develop logic to match and reconcile records across different systems using keys, rules, or fuzzy matching techniques
- Design and implement processes for building and maintaining golden master records
- Support creation and maintenance of master data across domains such as customer, product, asset, etc
- Handle data deduplication and standardization
- Build scalable data pipelines using Azure Data Factory for ingesting, transforming, and cleansing data from multiple sources
- Ensure efficient data movement across staging, processing, and analytical layers
- Leverage Azure Synapse Analytics (optional) for advanced data processing and analytics
- Work closely with business analysts, data stewards, and application owners to understand data definitions and ownership
- Enforce data governance standards and best practices
- Monitor data workflows and optimize performance for large-scale processing
- Troubleshoot data issues and implement robust logging and monitoring
Qualification and Education Requirements:
- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field
- 5+ years of experience in data engineering, ETL development, or data integration
- Proven experience in data profiling, matching, and MDM (Master Data Management)
- Expertise in SQL for querying, transforming, and optimizing complex datasets
- Strong proficiency in Python or PySpark for data processing and pipeline development
- Experience with Azure Data Factory for building and managing data pipelines
- Familiarity with Azure Synapse Analytics is a plus
- Strong expertise in ETL/ELT tools (e.g., Talend, Informatica, SSIS, Apache NiFi)
- Familiarity with data quality frameworks and metadata management
- Strong communication skills in both Arabic and English
- Experience with data cataloging tools (e.g., Azure Purview, Alation)
- Knowledge of data modeling and normalization techniques
- Understanding of data privacy and compliance standards (GDPR, HIPAA, etc.)
- Familiarity with REST APIs and integrating with third-party data services
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