Data Quality

Job Title: Data Quality Transformation Specialist

Experience: 8–14 Years

Location: Bangalore / Chennai

Role Overview: We are seeking experienced professionals to support the digitisation and transformation of the Data Quality (DQ) landscape. The role focuses on reducing and replacing manual processes, particularly in areas such as metadata management and business term development. The candidate will work closely with technology teams to enhance existing DQ tools and frameworks.

Key Responsibilities:

• Drive transformation initiatives to modernise the Data Quality (DQ) ecosystem 
• Reduce manual processing through automation and digitisation of DQ activities
• Manage and enhance metadata frameworks, including business glossary and data definitions
• Develop, standardise, and maintain business terms and data quality rules
• Collaborate with technology teams to enhance DQ tools such as Rosetta and DQMA
• Identify opportunities for process optimisation and efficiency improvements
• Support implementation of best practices in data governance and data quality management
• Work with stakeholders across business and technology to align DQ initiatives with organisational goals

Required Skills & Experience:

• 8–14 years of experience in Data Quality, Data Governance, or related domains 
• Strong understanding of metadata management and business glossary frameworks
• Hands-on experience with Data Quality tools (e.g., Rosetta, DQMA, or similar platforms)
• Experience in digitisation and transformation initiatives
• Strong analytical and problem-solving skills
• Ability to work collaboratively with cross-functional teams (Business & Technology)
• Excellent communication and stakeholder management skills

Preferred Qualifications:

• Experience in financial services or consulting environments
• Familiarity with data governance frameworks and regulatory requirements
• Exposure to automation tools or data engineering concepts

Responsibilities

• Lead end-to-end execution of projects and cross-functional deliverables for Data Quality.
• Collaborate closely with departmental peers and stakeholders to ensure seamless operational continuity.
• Monitor core performance KPIs, troubleshoot bottlenecks, and implement optimization protocols.
• Champion high quality standards, peer reviews, and comprehensive team documentation.