What are the responsibilities and job description for the Azure Databricks Architect - Fulltime position at Acunor Infotech?
Lead Architect Azure & Databricks
Location: 100% Remote
Working Hours: EST
Employment Type: Full-Time
Work Authorization: Visa-independent candidates only.
Role Overview
Acunor is seeking an experienced Lead Architect with strong expertise in Microsoft Azure, Databricks, and modern Data & AI platforms. This role will design and deliver scalable, secure, high-performing enterprise data solutions while working closely with business stakeholders, engineering teams, and clients.
Key Responsibilities
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Architect end-to-end data and analytics solutions on Azure and Databricks.
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Design scalable platforms supporting batch, streaming, and real-time analytics.
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Lead solution design discussions, architecture reviews, and technical governance.
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Define data lake, data warehouse, lakehouse, and data mesh architectures.
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Translate business requirements into practical technical solutions.
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Establish platform security, governance, and compliance standards.
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Design data integration frameworks using Azure-native services and Databricks.
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Drive performance optimization, cloud cost management, and modernization initiatives.
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Provide technical leadership and mentor engineering teams.
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Support proposal development, effort estimation, and client presentations.
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Ensure alignment with enterprise architecture standards and best practices.
Required Technical Skills
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Azure: Azure Data Factory, Azure Databricks, ADLS Gen2, Azure Synapse Analytics, Azure SQL Database, Azure Event Hub, Azure Service Bus, Azure Functions, Azure Key Vault, Azure Monitor, and Microsoft Entra ID.
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Databricks: Lakehouse Architecture, Delta Lake, Unity Catalog, Databricks Workflows, Structured Streaming, Medallion Architecture, cluster optimization, and performance tuning.
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Data Engineering: Python, PySpark, SQL, data modeling, ETL/ELT frameworks, data warehousing, and real-time data processing.
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DevOps and Automation: Azure DevOps, CI/CD pipelines, Git, and Infrastructure as Code. Terraform is preferred.
Required Qualifications
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Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
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10 years of experience in Data Engineering, Cloud Architecture, or Solution Architecture.
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5 years of hands-on experience with Azure cloud services.
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4 years of hands-on experience with Databricks and Spark-based solutions.
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Demonstrated experience designing enterprise-scale data platforms.
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Experience working with large-scale structured and unstructured datasets.
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Strong stakeholder management and client-facing communication skills.