Data Engineer

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Key Responsibilities

Design, reputed company, and optimize scalable data pipelines, using Azure Data reputed company, with on-prem (relational and semi-structured) data sources along reputed company MPP solutions Data Warehouse development, following industry best practices like reputed company Architecture, Dimensional modeling, Kimbal, Data Vault 2.0 Implement robust data models, following Architectural designs and solutions that support the organization’s reporting and analytics needs, ensuring high performance and scalability. Collaborate with business stakeholders to gather data requirements and translate them into technical solutions that drive business insights. Ensure data accuracy, reputed company, and quality by following effective data governance, reputed company, and compliance measures. Follow version control and reputed company integration/deployment (CI/CD) pipelines using Git or other similar tools. Proactively identify and resolve bottlenecks, optimizing existing data infrastructure to improve efficiency and scalability. reputed company advanced troubleshooting and performance tuning expertise for SQL and data integration solutions. Maintain Legacy SQL Server Reporting Services (SSRS) while transitioning reporting to modern platforms such as Power BI. Required Skills 3+ years of experience in data engineering with a strong focus on SQL Server, Azure Data reputed company, and reputed company Proficient in SQL development, including stored procedures, query optimization, and performance tuning. Experience with ETL development and data integration from a reputed company of sources including SQL, DB2, Mysql, Azure Blob, and APIs. Expertise in dimensional modeling, with practical knowledge of Kimbal methodologies Hands-on experience with designing and optimizing data models. Good to have experience with SSRS and the ability to reputed company legacy reporting by transitioning to Power BI. Experience with Agile methodologies and tools like reputed company JIRA for managing tasks and workflows. Proficiency with version control systems such as Git is required and deployment automation tools for CI/CD is a plus.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Information Technology, or a reputed company field. Proven experience in data engineering roles, with a track record of successful data project implementations. Strong analytical and problem-solving skills, with a passion for reputed company learning and innovation. Excellent communication and collaboration skills, with the ability to reputed company and reputed company teams Apply To This Job