Job Description

Title: Lead Data Engineer

A large-scale project that would process 100s TB of ERP data and other relevant data. Auditors would use this processed information to opine on the client engagements and provide value-added services to their clients. The project currently uses Azure data technologies and Databricks.

What Candidate Will Do:

• Design, build, and manage scalable data architectures using Databricks and Azure data technologies.
• System Design and implement modern data lake house solutions, ensuring seamless data integration, storage, and processing.
• Collaborate with cross-functional teams to gather and translate business requirements into effective technical designs.
• Ensure data quality and governance practices are implemented throughout the data lifecycle.
• Optimize data workflows for performance, reliability, and security using Azure one lake, Databricks Workflow and Databricks Compute, Unity catalog, Azure Synapse and PowerBI.
• Develop and enforce best practices in data modeling, pipeline design, and storage architecture.
• Conduct regular assessments of data systems to identify and address performance bottlenecks or areas for improvement.

Must-Have:

• 12+ Years of total IT experience in Data engineering and Data warehouse project development.
• 6+ years of hands-on experience with Azure Databricks and expertise in PySpark & Python development .
• Proven expertise in designing and managing scalable data architectures. Experience in Databricks Serverless is plus.
• 6+ years’ experience with Azure Synapse, Data Factory, and other Azure data technologies.
• 8+ years’ experience in data modeling,
• 6+ Years experience with Data pipelines design and implementation, and cloud storage architecture.
• Deep understanding of data quality and governance practices, and hands-on with Data quality and governance using Unity catalog or azure purview.
• Ability to collaborate with cross-functional teams and translate business requirements into technical designs.

Nice-to-Have:

• Familiarity with other modern data processing tools and technologies.
• Previous experience in a similar role working with large-scale data systems.

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