Lead Data Engineer/Data Integration Lead

Role Overview: As a Lead Data Engineer / Data Integration Lead at NotionMindz Technology LLP, you will play a crucial role in spearheading data initiatives. Your responsibilities will include designing, developing, and leading the implementation of robust data integration solutions, data warehousing operations, and reporting frameworks. You will need to leverage your expertise in SQL, RDBMS, ETL/ELT tools, and project leadership abilities to translate complex business requirements into tangible data solutions. Key Responsibilities: - Demonstrate expert-level knowledge and hands-on capability in SQL Server, including complex SQL query writing, object creation and management, and performance optimization of database/data warehouse operations. - Possess a strong understanding of Transactional and Dimensional Data Modeling concepts, including Star Schema, Facts, Dimensions, and their relationships. - Design, build, and optimize scalable data pipelines using Azure Data Factory and Azure Databricks, orchestrating complex data workflows and implementing dynamic and parameterized pipelines. - Utilize Spark-based data transformations within Databricks for large-scale data integrations, ensuring efficiency and performance. - Provide consultative advice to customers on best practices for data visualization and reporting. - Act as a primary interface with the customer directly on a daily basis, managing expectations and ensuring clear communication. - Technically lead a team of data developers and testers, providing guidance, mentorship, and support. - Possess a good understanding of SDLC practices, including source control, version management, and the usage of Azure DevOps. Qualification Required: - 8-12+ years of progressive experience in Data Engineering, Data Warehousing, or Data Integration roles, with significant experience in a lead capacity. - Expert-level knowledge in RDBMS (SQL Server) and strong SQL query writing, object management, and performance optimization skills. - Strong understanding of ETL concepts and hands-on exposure to SSIS, Azure Data Factory, Azure Databricks, or Airflow. - In-depth expertise in Azure Data Factory and Azure Databricks, including building scalable data pipelines, workflow orchestration, dynamic pipelines, and Spark-based transformations. - Hands-on experience with Databricks Unity Catalog for centralized data governance, access control, and data asset management. - Expert-level knowledge in Power BI and/or Azure Analysis Services. - Good understanding of SDLC practices, source control, version management, Azure DevOps, and CI/CD. - Strong data analysis skills for troubleshooting, deriving metrics, and providing insights. - Demonstrated ability to technically lead a team, perform design and code reviews. - Excellent presentation and communication skills (written and verbal) to express technical ideas and solutions clearly to both technical and functional audiences. Role Overview: As a Lead Data Engineer / Data Integration Lead at NotionMindz Technology LLP, you will play a crucial role in spearheading data initiatives. Your responsibilities will include designing, developing, and leading the implementation of robust data integration solutions, data warehousing operations, and reporting frameworks. You will need to leverage your expertise in SQL, RDBMS, ETL/ELT tools, and project leadership abilities to translate complex business requirements into tangible data solutions. Key Responsibilities: - Demonstrate expert-level knowledge and hands-on capability in SQL Server, including complex SQL query writing, object creation and management, and performance optimization of database/data warehouse operations. - Possess a strong understanding of Transactional and Dimensional Data Modeling concepts, including Star Schema, Facts, Dimensions, and their relationships. - Design, build, and optimize scalable data pipelines using Azure Data Factory and Azure Databricks, orchestrating complex data workflows and implementing dynamic and parameterized pipelines. - Utilize Spark-based data transformations within Databricks for large-scale data integrations, ensuring efficiency and performance. - Provide consultative advice to customers on best practices for data visualization and reporting. - Act as a primary interface with the customer directly on a daily basis, managing expectations and ensuring clear communication. - Technically lead a team of data developers and testers, providing guidance, mentorship, and support. - Possess a good understanding of SDLC practices, including source control, version management, and the usage of Azure DevOps. Qualification Required: - 8-12+ years of progressive experience in Data Engineering, Data Warehousing, or Data Integration roles, with significant experience in a lead capacity. - Expert-level knowledge in RDBMS (SQL Server) and strong SQL query writing, object management, and performance optimization skills. - Strong understanding of ETL concepts and han