PRINCIPAL CONSULTANT – Finance Data – Data Modeller Exp – 10+ Yrs Location – Bangalore, Pune, Hyderabad, Chennai, Gurgaon Mode of Work – Hybrid ROLE DESCRIPTION As a Finance Data Modeler, you'll work at the forefront of designing and development the finance data models in the Finance Data space which is crucial for the Finance Data program in building a self-service platform for the distribution of trusted data for Finance. In this role, you'll collaborate with Senior stakeholders in across the bank, breaking down complex challenges and developing innovative approaches and solutions. You'll be joining an exceptionally talented and supportive team, united by a shared mission to shape the future of data modelling and architecture design in the financial data space. We offer competitive compensation and the opportunity to make a tangible impact, powered by Organization 's recognized brand and industry-leading capabilities. If you have an entrepreneurial spirit and are passionate about data privacy, we'd love to hear from you. Let's discuss how your expertise can help us push the boundaries of what's possible KEY RESPONSIBILITIES Assist in the design and development of conceptual, logical, and application data models in line with the organization’s Future State Finance Data Asset Strategy. Collaborate with Finance business teams to enhance understanding, interpretation, design, and implementation. Support Finance business and change teams in transitioning to target state data models and Data Asset delivery, focusing on improving current data feeds and resolving data issues. Develop data modelling schemas that align with Enterprise data models and support Finance Data Assets. Participate in data modelling and data architecture governance forums. Ensure Finance data models align with Enterprise data models and adhere to Enterprise Architecture principles and standards Serve as a subject matter expert in Finance data modelling. Contribute to model development planning and scheduling. Continuously improve the data modelling estate, ensuring adherence to risk management, control measures, security protocols, and regulatory compliance standards. Advise and support Finance modelling data requirements for new use cases and data changes. Create and maintain a range of data modelling documents, including model requirements, data flow diagrams, data catalogues, data definitions, design specifications, data models, traceability matrices, data quality rules, and more. Translate Finance business requirements into data modelling solutions and Finance Data Assets. Conduct continuous audits of data models and refine them as needed, reporting any challenges, issues, or risks to senior management. Seek opportunities to simplify, automate, rationalize, and improve the efficiency of Finance IT and modelling solutions. Update and maintain key modelling artefacts, such as Confluence, SharePoint documents, reports, roadmaps, and other domain artefacts. Provide data modelling and technical advice, maintaining ongoing relationships. Provide timely feedback to ensure that model development or modification meets business needs. Communicate data modelling solutions to both technical and non-technical audiences, ensuring the communication style is appropriate for the intended audience. Support cross-program and cross-group Data Assets execution and delivery strategies, opportunities, and problem resolution. KEY ACCOUNTABILITIES Continuously improve the data modelling estate, ensuring adherence to risk management, control measures, security protocols, and regulatory compliance standards. Conduct continuous audits of data models and refine them as needed, reporting any challenges, issues, or risks to senior management. Ensure Finance data models align with Enterprise data models and adhere to Enterprise Architecture principles and standards. Provide timely feedback to ensure that model development or modification meets business needs. Support cross-program and cross-group Data Assets execution and delivery strategies, opportunities, and problem resolution. THE PREFERRED CANDIDATE WILL: Be a self-motivator working in a team of Organization and client colleagues Be good at problem solving Be comfortable working closely with stakeholders (both technical and non-technical) to perceive new and better ways of working Be adaptable and able to work across multiple Business Functions in parallel under pressure to tight deadlines Be able to demonstrate strong collaboration skills to align and define strategies that meet the program requirements MANDATORY SKILLS AND EXPERIENCE Business Minimum of 5 years of experience in data management and modelling within the Financial Services sector, ideally in a Treasury or Finance role, or a related front office environment. Demonstrated expertise in designing data models (conceptual, logical, and application/messaging) with appropriate phasing, transitions, and migrations. Strong understanding of managing data as a product across various enterprise domains and technology landscapes. Solid knowledge of business, data, application, and technology architectural domains. Excellent communication skills with the ability to influence and present data models and concepts to both technical and business stakeholders. Proven ability to work effectively in a matrixed environment, collaborating with data modellers from other domains to create shared and reusable data assets. Technical Experience with Agile and Scrum methodologies in a large-scale Agile environment, including active participation in daily standups and progress reporting. Knowledge of reference and master data management. Proficiency with data modelling tools such as Visual Paradigm, ERwin, PowerDesigner, ER Studio, etc. Understanding of data modelling standards and technical documentation using ERD, UML, or BIAN. Ability to deliver solutions that provide organizational benefits. Strong analytical and problem-solving skills, with the ability to work independently and take ownership of key deliverables. PREFERRED SKILLS AND EXPERIENCE Proven experience in a large, global banking setting is highly valued. Familiarity with data standards, governance, strategy, and lineage is a plus. Exposure to cloud platforms (GCP, AWS, Azure) and big data solutions is advantageous. Knowledge of issue and data quality management, prioritization, business case development, remediation planning, and solution delivery. Experience with data governance initiatives like lineage, masking, retention policies, and data quality. Strong analytical and problem-solving skills, with the ability to work independently and take ownership of key deliverables. Open-minded approach to problem-solving, ensuring pragmatic and effective designs. Familiarity with ETL architectures and tools, including data virtualization and API integration, is desirable. Show more Show less