Microsoft Cloud Data Engineering Lead

Position Overview:

The Microsoft Cloud Data Engineering Lead role is ideal for an experienced Microsoft Cloud Data Engineer who will architect, build, and optimize data platforms using Microsoft Azure technologies. The role requires the candidate to have deep technical expertise in Azure data services, strong leadership capabilities, and a passion for building scalable, secure, and high-performance data ecosystems.

Key Responsibilities:

• Lead the design, development, and deployment of enterprise-scale data pipelines and architectures on Microsoft Azure.
• Manage and mentor a team of data engineers, promoting best practices in cloud engineering, data modeling, and DevOps.
• Architect and maintain data platforms using Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory, Azure Databricks, and Azure SQL/SQL MI.
• Develop robust ETL/ELT workflows for structured and unstructured data using Azure Data Factory and related tools.
• Collaborate with data scientists, analysts, and business units to deliver data solutions supporting advanced analytics, BI, and operational use cases.
• Implement data governance, quality, and security frameworks, leveraging tools such as Azure Purview and Azure Key Vault.
• Drive automation and infrastructure-as-code practices using Bicep, ARM templates, or Terraform with Azure DevOps or GitHub Actions.
• Ensure performance optimization and cost-efficiency across data pipelines and cloud environments.
• Stay current with Microsoft cloud advancements and help shape cloud strategy and data architecture roadmaps.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
• Experience:
  • 7+ years of experience in data engineering, including 3+ years working with Microsoft Azure.
  • Proven leadership experience in managing and mentoring data engineering teams.
• Skills:
  • Expert knowledge of Azure Data Lake, Synapse Analytics, Data Factory, Databricks, and Azure SQL-based technologies.
  • Proficiency in SQL, Python, and/or Spark for data transformation and analysis.
  • Strong understanding of data governance, security, compliance (e.g., GDPR, PCIDSS), and privacy in cloud environments.
  • Experience leading data engineering teams or cloud data projects from design to delivery.
  • Familiarity with CI/CD pipelines, infrastructure as code, and DevOps practices within the Azure ecosystem
  • Familiarity with Power BI and integration of data pipelines with BI/reporting tools
• Certifications :
  • Microsoft Certified: Azure Data Engineer Associate or Azure Solutions Architect Expert.