Data Engineer

Job Description

• Design, develop, and maintain scalable data warehouse solutions to meet business needs.
• Build efficient and reliable ETL/ELT pipelines to process and integrate data from diverse sources.
• Develop and manage Power BI dashboards and reports to provide actionable insights.
• Collaborate with cross-functional teams to define data requirements and implement solutions.
• Optimize database performance, ensure data integrity, and maintain high availability.
• Implement and enforce data governance policies to secure sensitive information.
• Stay current with emerging technologies and trends in data engineering and analytics.

Qualifications

• Bachelor's or master's degree in computer science, Data     Engineering, or related field.
• Proficiency in data warehousing concepts and tools     (e.g., Snowflake, Redshift, Big Query).
• Strong expertise in Power BI, including dashboard development and DAX.
• Solid understanding of SQL and relational database management systems.
• Experience with programming languages like Python or Scala for data processing.
• Familiarity with cloud platforms such as Azure, AWS, or Google Cloud.
• Knowledge of data modeling, ETL processes, and real-time data processing.
• Excellent problem-solving skills and attention to detail.
• Data and Integration Services: Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Azure SQL, Cosmos DB, Azure     Data Lake, Blob Storage, Purview, Fabric, Elastic Jobs, Logic Apps, API     Management, Function Apps, Key Vault, Service Bus, Event Hub, Log     Analytics, SQL Server Integration Services (SSIS), Apache Airflow,     Snowflake.
• ML and AI Services: Azure ML, Azure OpenAI Service, Azure AI Search (Cognitive Search), Azure Speech Service, Azure AI-Language, Azure AI Document Intelligence.

• Experience with big data technologies (e.g., Hadoop, Spark).
• Familiarity with data orchestration tools like Apache     Airflow or similar.
• Certification in relevant technologies (e.g., Microsoft     Power BI, AWS Data Analytics).
• Exposure to Agile methodologies and project management practices.

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