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Azure Data Engineer
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2 - 5 years of experience
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Bachelor’s degree in computer science, Information Technology, or a related field.
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Strong experience with Azure Data Factory, Azure Synapse Analytics, and other Azure data services.
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Proficiency in SQL and data querying languages.
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Expertise in dimensional modeling and data warehousing concepts.
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Hands-on experience with ETL processes and tools.
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Familiarity with analytics and reporting tools, such as Power BI.
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Knowledge of cloud computing concepts and services, especially within the Microsoft Azure ecosystem.
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Strong problem-solving and troubleshooting skills.
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Certifications such as Microsoft Certified: Azure Data Engineer Associate are a plus.
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Data Modelling: Design and implement data models, including measures and dimensions, to support business intelligence and analytical reporting requirements.
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Azure Data Factory Development: Create, manage, and optimize data pipelines in Azure Data Factory to extract, transform, and load (ETL) data from various sources into the data warehouse.
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Dimensional Modelling: Develop and implement dimensional models for data warehousing, ensuring efficient storage and retrieval of data for analytical purposes.
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ETL Processes: Build and maintain ETL processes within Azure Data Factory to transform and cleanse data before loading it into the data warehouse.
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Integration with Analytics Services: Collaborate with data scientists and analysts to integrate Azure Data Factory with analytics services such as Azure Synapse Analytics, Azure Databricks, and Power BI.
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Data Quality and Governance: Implement data quality checks and governance measures to ensure the accuracy, completeness, and consistency of data stored in the data warehouse.
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Performance Tuning: Monitor and optimize data warehouse performance, including query performance and data loading processes, to meet performance and scalability requirements.
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Security and Compliance: Implement security measures for data access and ensure compliance with data governance policies and regulatory requirements.
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Documentation: Create and maintain documentation for data models, ETL processes, and data warehouse configurations.
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Collaboration: Work closely with business analysts, data scientists, and other stakeholders to understand reporting requirements and deliver effective data solutions.
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MongoDB certification (e.g., MongoDB Certified Database Administrator)
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Experience with MongoDB databases. (Minimum of 3 years experience as DBA)
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Experience with other NoSQL DB (e.g. CosmoDB, DynamoDB, Cassandra etc)
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Familiarity with containerization technologies (e.g., Docker, Kubernetes).
