DARE TO BE A PART OF THE CHALLENGE! COME AND JOIN OUR TEAM TOGETHER WE CAN MAKE THE DIFFERENCE!
Did you know that Accenture is leading the digital transformation in the World?
Accenture is a leading global professional services company, providing a broad range of services and solutions in strategy, consulting, digital, technology and operations. Our main purpose is to collaborate with our clients, so they can become high-performance businesses. Accenture is present in more than 200 cities, 49 countries and approximately 732,000 employees worldwide.
Offer
-
Career development according to your profile and interests.
-
Work in one of the best companies and feel proud.
-
Access to an innovative methodology and tools.
-
Direct contact with experts worldwide.
-
Use of work schemes and cutting-edge technologies.
-
Constant training.
-
Work environment based on teamwork and collaboration.
-
Participation in International Projects
Accenture does not discriminate based on race, religion, color, sex, age, disability, nationality, sexual orientation, gender identity or expression, or for any other reason covered by local law.
As a Data Modeler, you will be responsible for working closely with key business representatives, data owners, end users, application designers, and data architects to model both current and new data. Your day-to-day activities will involve analyzing data requirements, designing data structures, and ensuring alignment with business needs. You are expected to be a subject matter expert, collaborate effectively with and manage the team to perform, take responsibility for team decisions, engage with multiple teams, and contribute to key decisions. Providing solutions to problems that impact multiple teams will be a critical part of your role.
Master proficiency in Data Modeling Techniques and Methodologies is required, specifically Medallion architecture.
Financial Industry experience is highly desirable.
Proficient utilization of Erwin or similar data modeling tool is mandatory.
Master proficiency in AI & Data Processes, Data Quality Tools & Methods, Data Taxonomy, and AI & Data Strategy is suggested.
