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We are looking for an experienced Data Architect to design and implement cutting-edge data solutions that meet the evolving needs of our enterprise. This role involves building secure, scalable, and high-performing data platforms while leveraging modern technologies and aligning with organizational goals. The ideal candidate will have expertise in cloud-based architecture, data governance, and advanced analytics, driving innovation across diverse business functions.
Job Responsibility:
Develop comprehensive data architecture strategies for advanced analytics and big data solutions using Azure Databricks
Design and implement Databricks Delta Lake-based Lakehouse architecture, utilizing PySpark Jobs, Databricks Workflows, Unity Catalog, and Medallion architecture
Optimize and configure Databricks clusters, notebooks, and workflows to ensure efficiency and scalability
Integrate Databricks with Azure services such as Azure Data Lake Storage, Azure Data Factory, Azure Key Vault, and Microsoft Fabric
Establish and enforce best practices for data governance, security, and cost management
Collaborate with data engineers, analysts, and business stakeholders to translate functional requirements into robust technical solutions
Provide technical mentoring and leadership to team members focused on Databricks and Azure technologies
Monitor, troubleshoot, and enhance data pipelines and workflows to maintain reliability and performance
Ensure compliance with organizational and regulatory standards regarding data security and privacy
Document configurations, processes, and governance standards to support long-term scalability and usability
Requirements:
Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field
At least 7 years of progressive experience in data engineering and modeling, including 2 years in an architecture or lead technical role
Expertise in architecting enterprise-level cloud data platforms using Azure
Hands-on experience with Databricks Delta Lake, PySpark Jobs, Databricks Workflows, Unity Catalog, and Medallion architecture
Strong knowledge of data security principles and best practices
Familiarity with Databricks monitoring tools and performance optimization techniques
Proficiency in DevOps and Infrastructure-as-Code practices, such as CI/CD pipelines and automated deployment frameworks
Nice to have:
Certifications such as Microsoft Certified: Azure Data Engineer Associate or Databricks Certified Data Engineer are highly desirable