New

Azure Data Engineer

Cognizant North America
United States, Texas, Dallas
Feb 12, 2025
Job Summary We are seeking an experienced Architect with 8 to 11 years of experience in Data Warehousing ETL SQL Data Integration Microsoft SSIS and Unix Shell Scripting. The ideal candidate will have a strong background in Finance & Accounting domains. This hybrid role offers the opportunity to work on innovative projects and make a significant impact on our data management strategies. Responsibilities Lead the design and implementation of data warehousing solutions to support business intelligence and analytics needs. Oversee the development and maintenance of ETL processes to ensure efficient data integration and transformation. Provide expertise in SQL to optimize database performance and ensure data accuracy. Collaborate with cross-functional teams to gather requirements and deliver data solutions that meet business needs. Develop and maintain data integration workflows using Microsoft SSIS. Utilize Unix Shell Scripting to automate data processing tasks and improve system efficiency. Ensure data quality and integrity through rigorous testing and validation processes. Monitor and troubleshoot data warehousing and ETL processes to ensure smooth operation. Stay updated with the latest industry trends and technologies to continuously improve data management practices. Provide technical guidance and mentorship to junior team members. Work closely with Finance & Accounting teams to understand their data requirements and deliver tailored solutions. Contribute to the development of data governance policies and procedures. Document all data warehousing and ETL processes for future reference and compliance. Qualifications Possess strong experience in Data Warehousing Concepts and Scheduling Basics. Demonstrate proficiency in ETL SQL and Data Integration techniques. Have hands-on experience with Microsoft SSIS and Unix Shell Scripting. Exhibit a solid understanding of Finance & Accounting domains. Show excellent problem-solving and analytical skills. Display strong communication and collaboration abilities. Have a keen eye for detail and a commitment to data quality. Be adaptable to a hybrid work model and comfortable with day shifts. Bring a proactive approach to learning and applying new technologies. Demonstrate the ability to work independently and as part of a team. Possess a strong sense of responsibility and ownership of tasks. Show a commitment to continuous improvement and professional development. Have a track record of delivering high-quality data solutions on time.