Lead Azure Data Engineer

Job Summary

Lead Azure Data Engineer.

Responsibilities

• Lead Azure Data Engineer

Requirements

• 8+ years of overall IT experience with minimum 5 years leading a small team of Azure Data Engineers
• 5+ years of experience with Database Development and Data Integration initiatives
• 5+ years of experience building ETL/ELT solutions using Azure data integration tools such as Azure Data Factory, Azure Functions, Logic Apps and Databricks
• Highly experienced with DLTs, Unity Catalog, Databricks SQL and Workflows.
• Hands-on experience in Azure Databricks Pyspark to develop ETL pipelines,
• Strong experience reading and writing queries in Azure or any relational database is required.
• Prior knowledge of best practices in SDLC and use of source control management tool preferably Azure DevOps to GitHub integration is highly desired.
• Experience working in a production environment for multiple clients in a compliance industry.
• Ability to work in a team through the implementation and adoption of data management framework.
• Ability to translate customer needs into technical requirements.
• Good verbal and written communication skills
• Excellent interpersonal skills
• Skill in troubleshooting and problem solving.
• Ability to work in an environment which is driven by process governance.

Preferred Qualifications

• Bachelor s degree preferably in Computer Science, Technology or Engineering
• Experience working with data management teams supporting Pharma field operations
• Experience in data-centric implementations such as SFA/CRM and Business Intelligence Tools
• Experience with Salesforce.com/Veeva or a similar CRM system
• Prior experience with Veeva Network
• Experience in Pharmaceutical and Life sciences implementations and awareness of commonly used data sources for Customer Master and Sales information
• Microsoft Azure Data Engineer Associate - DP-203 Certification and Training
• Databricks Certified Data Engineer Associate Certification
• Experience with Agie methodologies and tools (e.g., Jira, Confluence)

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