Join our Engineering practice as a Consultant, where you'll unlock the value hidden within vast datasets. We provide strategic guidance and implementation services to help companies manage data from diverse sources, transforming it into actionable insights for data-driven decision-making and a competitive edge. Our expertise spans business intelligence, data management, performance management, and advanced technologies like big data, cloud, cognitive computing, and machine learning.

In this role within our Technology & Transformation Team, you will cultivate strong client and team relationships, consistently aiming to exceed expectations. This is an opportunity to contribute to innovative solutions in a dynamic environment.

As a Consultant, you will focus on creating and maintaining robust data models using industry-standard notations like UML Class Models. You will apply expertise in relational, dimensional, and modern data modelling techniques to design solutions for complex data structures across enterprise systems and cloud platforms. Your responsibilities will include developing enterprise data architecture, defining data governance frameworks, and harmonizing data provisioning. You will leverage expert proficiency with leading data modelling tools and manage projects effectively, building strong stakeholder relationships across various functions.

We are seeking professionals with 6-9 years of experience, specializing in data modelling and data architecture within the financial services industry, particularly in Private or Retail Banking. A deep understanding of financial products, processes, and the data lifecycle is essential. Proficiency in data modelling tools such as Power Designer, ER/Studio, or Erwin is required. Strong capabilities in project and stakeholder management are crucial, alongside a solid grasp of database technologies, big data, and data integration patterns. Candidates should possess excellent communication and problem-solving skills. A B.Tech/BE in Computer Science or Information Technology is preferred.