Job Summary
We are seeking a Sr. Developer with 8 to 10 years of experience in ETL Data WareHousing Concepts Data Lake Concepts Informatica Cloud Scheduler Cloud DWH SQL Data Integration Informatica Cloud and Unix Shell Scripting. The ideal candidate will have domain expertise in Cards & Payments. This is a hybrid work model with day shifts and no travel requirements.
Responsibilities
Develop and maintain ETL processes to ensure efficient data integration and transformation.Design and implement data warehousing solutions to support business intelligence and analytics.Utilize Data Lake Concepts to manage and store large volumes of structured and unstructured data.Schedule and monitor data workflows using Informatica Cloud Scheduler.Implement and manage Cloud DWH solutions to ensure scalable and secure data storage.Write and optimize SQL queries for data extraction transformation and loading.Integrate data from various sources to create a unified data repository.Use Informatica Cloud to automate and streamline data integration processes.Develop Unix Shell Scripts to automate repetitive tasks and improve system efficiency.Collaborate with cross-functional teams to understand data requirements and deliver solutions.Ensure data quality and integrity by implementing robust validation and error-handling mechanisms.Provide technical support and troubleshooting for data-related issues.Stay updated with the latest industry trends and technologies to continuously improve data solutions.
Qualifications
Possess strong expertise in ETL processes and tools.Have in-depth knowledge of Data WareHousing and Data Lake Concepts.Demonstrate proficiency in Informatica Cloud Scheduler and Cloud DWH.Exhibit advanced SQL skills for data manipulation and querying.Show experience in data integration and Informatica Cloud.Have hands-on experience with Unix Shell Scripting.Understand the Cards & Payments domain thoroughly.Display excellent problem-solving and analytical skills.Communicate effectively with technical and non-technical stakeholders.Work independently and as part of a team.Adapt to a hybrid work model and manage time efficiently.Stay committed to delivering high-quality data solutions.Continuously learn and apply new technologies to enhance data processes.