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Capco

Data Modeler

Sorry, this job was removed at 02:12 p.m. (IST) on Tuesday, Sep 09, 2025
Remote or Hybrid
Hiring Remotely in India
Remote or Hybrid
Hiring Remotely in India

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Job Title: Data Modeler

 About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the  British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. 

WHY JOIN CAPCO?

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

MAKE AN IMPACT

Requirements:

Job Title: Data Modeler

Experience: 12+ years

Location: Hyderabad

    • Roles & Responsibilities

      • Minimum of 10 years' experience of Data management and modelling solutions working as a Data Modeller within the Financial Services sector is essential; preferably in a Treasury/Finance function and or related front office environment.
      • A proven track record working in a large and global banking environment is desirable.
      • Demonstrate experience in design data modelling solutions (conceptual, logical and application/messaging) with corresponding phasing, transitions, and migrations where necessary.
      • Good understanding of managing 'data as a product (asset)’ principle across enterprise domains and technology landscapes.
      • Good understanding of architectural domains (business, data, application, and technology)
      • Good communication skills with the ability to influence and present data models (as well as concepts) to technology and business stakeholders.
      • Good collaboration skills with the ability to demonstrate experience achieving outcomes in a matrixed environment partnering with data modellers from other domains to build and join shared and reusable data assets.
      • Experience of working with Agile and Scrum in a large scalable Agile environment. This should include participation and progress reporting in daily standups.
      • Data standards, data governance, data strategy and data lineage would be advantageous in this role.
      • Knowledge of reference/master data management
      • Cloud exposure to solutions implemented in either GCP, AWS or Azure would be beneficial as well as having exposure to big data solutions would be advantageous.
      • Experience working with leading data modelling tools modelling documentation using tools such as Visual Paradigm, ERwin, PowerDesigner, ER Studio etc.
      • Knowledge of data modelling standards and modelling technical documentation using Entity Relationship Diagrams (ERD) or Unified Modelling language (UML) or BIAN.
      • Results oriented with ability to produce solutions that deliver organisational benefit.
      • Understanding of issue and data quality management, prioritisation, business case development, remediation planning and tactical or strategic solution delivery
      • Exposure with data governance initiatives such as lineage, masking, retention policy, and data quality
      • Strong analytical skills and problem-solving, with the ability to work unsupervised and take ownership for key deliverables.
      • Exposure with ETL architectures and tools, including data virtualisation, integration with APIs is desirable.

      Approach problems with an open mind and challenge to ensure appropriate pragmatic clean designs.

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