Azure Data Engineer

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We are looking for an experienced Azure Data Engineer to design, implement, and manage data solutions using the full Azure data services stack. The ideal candidate will have at least five years of operational experience in managing, monitoring, securing, and ensuring the privacy of data, with a strong focus on optimizing business outcomes through data-driven insights. The role demands expertise in Azure data services and Microsoft certification is required.

Key Responsibilities:

• Design and implement scalable, secure, and reliable data management architectures using the Azure data services stack (e.g., Azure SQL Database, Azure Data Lake, Azure Synapse Analytics, Azure Databricks, and Cosmos DB).

• Develop and maintain data pipelines for ETL/ELT processes using Azure Data Factory and Azure Databricks to ingest, transform, and load structured and unstructured data from various sources.

• Ensure the management, monitoring, and performance tuning of data storage solutions to meet performance and cost-efficiency objectives.

• Implement robust security controls and privacy measures to protect sensitive data, ensuring compliance with organizational and regulatory requirements, including Azure Active Directory (AAD) and Azure Key Vault integration.

• Monitor data infrastructure performance, availability, and cost using Azure Monitor, Azure Log Analytics, and other relevant Azure monitoring tools.

• Collaborate with data scientists, analysts, and business stakeholders to design and implement data solutions that enable advanced analytics and reporting.

• Perform data modeling and optimization to support business intelligence (BI) and data visualization tools like Power BI and Azure Synapse Analytics.

• Participate in continuous improvement initiatives and provide insights on best practices for data governance, data security, and efficient data operations.

• Ensure compliance with data privacy standards such as GDPR and CCPA by integrating appropriate privacy measures into data solutions.

• Provide technical leadership, mentoring, and training to junior team members on Azure data services and engineering best practices.

Qualifications:

• 5+ years of operational experience in designing and implementing data solutions using Azure data services.

• Expertise with Azure data technologies, including Azure SQL Database, Azure Synapse Analytics, Azure Data Factory, Azure Data Lake, Cosmos DB, and Azure Databricks.

• Strong understanding of data security, privacy, and governance in a cloud environment, with practical experience in securing data with Azure Active Directory (AAD), Azure Key Vault, and Role-Based Access Control (RBAC).

• Proficiency in ETL/ELT processes, data integration, and data pipeline development using Azure Data Factory and Azure Databricks.

• Hands-on experience with data monitoring and cost management using Azure tools like Azure Monitor and Log Analytics.

• Solid understanding of SQL, T-SQL, and Python for data engineering and querying large datasets.

• Experience with data modeling, relational databases, and NoSQL databases.

• Familiarity with CI/CD pipelines for automating data deployment processes and version control in an Azure DevOps environment.

• Excellent communication skills with the ability to work collaboratively with cross-functional teams and stakeholders.

• Ability to obtain and maintain a Public Trust clearance

Certification Requirements:

• Microsoft Certified: Azure Data Engineer Associate is required.

• Additional certifications such as Azure Solutions Architect Expert or Azure Administrator Associate are a plus.

Preferred Qualifications:

• Experience with Power BI integration and data visualization.

• Familiarity with MLOps and integration with Azure Machine Learning.

• Experience with data privacy compliance standards like GDPR and CCPA.

Applied Information Sciences is an Equal Opportunity Employer and does not discriminate on the basis of race, national origin, religion, color, gender, sexual orientation, age, disability, protected veteran status, or any other basis covered by law. Employment decisions are based solely on qualifications, merit, and business need.