Data Quality
AI Summary
Leads data quality transformation initiatives, modernising the DQ ecosystem by reducing manual processes, enhancing metadata and business glossaries, and collaborating with technology teams.
About this role
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
Skills
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