Azure Data Architect Undefined

Must have experience in Azure Databricks and ADF, Azure Synapse, PySpark, SQL

JD:

Experience: 12 to 15 Years , Minimum 5+ Years of experience in Azure Data Architect

• Overall 15+ years in data analytics consulting and at least 10+ Senior Architect role within a consulting firm with a focus on data analytics, advanced analytics, Cloud
• 5-7+ years in designing, solutioning the Azure Databricks, PySpark, Data engineering, Data Integration, Data Orchestration and Data Marketplace.
• 7+ years’ experience in designing Azure data warehouse and Responsible for designing and implementing secure, scalable, and highly available cloud-based solutions and estimation on Azure Cloud.
• Cloud Architect with experience in Azure ADF, ADLS Gen2, Databricks, Synapse, PySpark
• Responsible for designing and implementing secure, scalable, and highly available cloud-based solutions and estimation on AWS and Azure Cloud
• Mandatory Experience in Azure Databricks and ADF, Azure Synapse and PySpark
• Bachelor’s or Master’s degree in Computer Science, Data Science, Business Analytics, or a related field.
• Hands on individual with ability to self-explore on market trends and provide POV on how it will have an impact on existing landscapes and suggest recommendations.
• Experience in within a consulting firm or similar environment, with a focus on cloud data analytics in the medical device industry other regulated industry preferred.
• Proficiency in data analytics tools and technologies, such as Python, R, SQL, and cloud platforms (e.g., AWS, Azure).
• Deep technical understanding of major cloud tools like Azure, Google Cloud Platform, AWS, data analytics technologies, methodologies, and best practices.
• Strong technical experience in major BI reporting tools like Power BI
• Excellent communication, presentation, and interpersonal skills.
• Proven track record of successfully leading and delivering data analytics projects from conception to completion for fortune clients
• Relevant certifications in Azure, Databricks and Big Data are a plus.
• Experience with integration of different data sources with Data Warehouse and Data Lake is required
• Experience in creating Data warehouse, data lakes for Reporting, AI and Machine Learning
• Understanding of data modelling and data architecture concepts
• To be able to clearly articulate pros and cons of various technologies and platforms
• Collaborate with clients to understand their business requirements and translate them into technical solutions that leverage AWS and Azure cloud platforms.
• Define and implement cloud governance and best practices.
• Identify and implement automation opportunities to increase operational efficiency.
• Data Fabric, Mesh, Lakehouse data implementation experience
• Conduct knowledge sharing and training sessions to educate clients and internal teams on cloud technologies.