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.

About the Job: We are looking for an experienced professional with at least 6+ years of hands-on experience with Databricks technology.

What Candidates Will Do:

• Design, build, and manage scalable data architectures using Databricks and Azure data technologies. 
• Architect and implement modern data lakehouse 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 Synapse, Data Factory, and Databricks. 
• 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:

• 10+ Years of total IT experience in Data engineering and Вata 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. 
• 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.