Senior Data Analyst

The core responsibilities for the job include the following:
Data Quality and Validation:
Perform profiling, rule checks, and data health assessments for Customer and Sales datasets.
Identify data gaps, inconsistencies, duplicates, and integrity issues; propose corrective actions.
Work with data owners and stewards to align on standards and definitions.
Track and report data quality KPIs.
Ground Truth and AI Enablement:
Collaborate with SMEs to gather ground truth for model training, labeling, and evaluation.
Validate datasets to ensure accurate representation of Customer and Sales processes.
Support feature validation, input-output checks, and pre-UAT reviews.
Requirements and Analysis:
Capture data, process, and reporting requirements for AI use cases.
Document data requirements, transformation rules, acceptance criteria, and test scenarios.
Map data flows across CRM, Sales, and Customer Master systems.
Compliance and Risk:
Ensure data minimization and proper handling of personal and confidential data.
Maintain risks, issues, and mitigation plans.
UAT and Delivery Support:
Prepare test cases tied to data rules and model requirements.
Execute UAT with focus on data accuracy; identify defects and drive closure.
Validate outputs against business logic and acceptance criteria.
Support deployment readiness and handover documentation.
Communication and Documentation:
Provide clear status updates, risks, and insights.
Maintain data dictionaries, quality rules, lineage, and test assets.
Update AI and data compliance trackers.
Requirements:
Strong experience working on data quality assessment and analysis/reporting
Hands-on big data handling, profiling, and quality experience.
Proven Data project management: planning, execution, defect management, and sign-off.
Excellent stakeholder management, facilitation, and communication skills.
Comfortable working in agile cross-functional teams.

Experience
10-12 yrs