Senior Data Analyst Data Quality & AI Enablement

Experience : 10+ Years

Location : Bangalore (Bagmane Solarium)

Mode of Work : Hybrid (3 Days Mandatory from Office)

Key Responsibilities :

Data Quality Management & Validation :

- Perform comprehensive data profiling, quality assessments, and health checks across Customer, Sales, CRM, and Master Data domains.

- Design, execute, and monitor data quality rules to identify anomalies, inconsistencies, duplicates, missing values, and integrity issues.

- Conduct root cause analysis for data quality issues and collaborate with data owners and technical teams to implement corrective actions.

- Define, maintain, and enhance data quality frameworks, standards, and monitoring processes.

- Track, measure, and report data quality KPIs and metrics through dashboards and executive reports.

- Ensure data consistency across multiple enterprise applications and systems.

AI Enablement & Ground Truth Validation :

- Partner with Business SMEs and AI/ML teams to gather, validate, and maintain high-quality ground truth datasets.

- Support data labeling, annotation, classification, and validation activities for AI model development and training.

- Validate input and output datasets to ensure alignment with business requirements and expected outcomes.

- Perform feature validation and data readiness assessments for AI and Machine Learning initiatives.

- Conduct pre-UAT reviews to ensure data quality and model readiness before deployment.

- Assist in model evaluation by validating predictions against business-defined acceptance criteria.

Business Requirements Analysis :

- Gather, analyze, and document business, data, and reporting requirements for AI and analytics initiatives.

- Translate business requirements into detailed functional specifications and data requirements.

- Define transformation rules, mapping documents, business rules, and acceptance criteria.

- Develop and maintain data flow diagrams across Customer Master, CRM, Sales, and downstream systems.

- Conduct impact assessments for changes affecting data quality, governance, and reporting.

Data Governance & Compliance :

- Ensure adherence to enterprise data governance standards, policies, and best practices.

- Maintain data dictionaries, business glossaries, metadata repositories, and lineage documentation.

- Support compliance requirements related to personal, confidential, and sensitive data handling.

- Implement data minimization principles and ensure proper usage of customer and sales data.

- Identify potential data risks and maintain risk registers, mitigation plans, and issue logs.

- Collaborate with governance teams to improve data stewardship and accountability.

UAT, Testing & Deployment Support :

- Design and execute test cases focused on data validation, business rules, and AI model outputs.

- Conduct User Acceptance Testing (UAT) and coordinate defect tracking, prioritization, and resolution.

- Validate system outputs against business logic, transformation rules, and acceptance criteria.

- Ensure deployment readiness through comprehensive testing and validation activities.

- Support production rollout activities and post-deployment verification.

- Prepare handover documents, knowledge transfer materials, and operational support artifacts.

Project & Stakeholder Management :

- Manage end-to-end data quality initiatives, including planning, execution, monitoring, and sign-off.

- Collaborate with business users, product owners, architects, engineers, data scientists, and governance teams.

- Facilitate workshops, requirement-gathering sessions, and data review meetings.

- Provide regular project status updates, risk assessments, and executive-level reporting.

- Support Agile delivery practices, including sprint planning, backlog grooming, and retrospectives.

Required Skills & Experience :

Technical Skills :

- 10+ years of experience in Data Analysis, Data Quality Management, Data Governance, or Data Management projects.

- Strong expertise in data profiling, data cleansing, reconciliation, validation, and quality monitoring.

- Experience working with large-scale datasets and Big Data platforms.

- Advanced SQL skills for data extraction, validation, and analysis.

- Hands-on experience with data quality tools and data governance frameworks.

- Strong understanding of Customer Data, Sales Data, CRM systems, and Master Data Management (MDM).

- Experience with data lineage, metadata management, and data cataloging concepts.

- Knowledge of AI/ML data preparation, ground truth creation, and validation processes.

- Familiarity with cloud-based data platforms and modern analytics ecosystems.

Project Management & Delivery :

- Proven experience managing Data Quality and Data Governance initiatives from planning through sign-off.

- Strong understanding of Agile and Scrum methodologies.

- Experience in defect management, risk tracking, issue resolution, and release management.

- Ability to prioritize multiple deliverables and manage competing business requirements.

Soft Skills :

- Excellent stakeholder management and communication skills.

- Strong analytical and problem-solving abilities.

- Ability to influence cross-functional teams and drive data quality improvements.

- Exceptional documentation and presentation skills.

- Strong attention to detail and commitment to data accuracy.

Preferred Qualifications :

- Experience supporting AI, Machine Learning, or Generative AI initiatives.

- Knowledge of Customer Master Data Management (MDM) frameworks.

- Exposure to enterprise CRM platforms such as Salesforce, SAP, Microsoft Dynamics, or similar systems.

- Experience with data governance and quality tools.

- Relevant certifications in Data Management, Data Governance, Agile, or Project Management will be an added advantage.

Success Criteria :

- Improved data quality scores across Customer and Sales domains.

- Accurate and validated datasets supporting AI initiatives.