Python Developer - Data Validation

Job Description – Data Validation Lead
Position: Data Validation Lead
Experience:5+ Years
Notice : Immediate
Location: Remote
Highlighted is mandatory skills
Role Overview
We are looking for an experienced Data Validation Lead with 5+ years of experience in data validation, data quality, and testing. The candidate will be responsible for leading data validation activities, ensuring data accuracy and integrity, and coordinating a team of 3 members.
The ideal candidate should have strong hands-on experience with Python-based data validation, data comparison, reconciliation, validation frameworks, and test automation. The candidate should also have strong leadership and communication skills to manage validation activities and deliverables.
Key Responsibilities
• Lead end-to-end data validation and reconciliation activities across data migration, integration, and transformation projects.
• Lead and mentor a team of 3 data validation/QA engineers.
• Define the overall data validation strategy, approach, scope, and execution plan.
• Review business and technical requirements and translate them into data validation scenarios and test cases.
• Develop and maintain Python-based data validation scripts and automation frameworks.
• Perform source-to-target data validation and reconciliation.
• Validate data completeness, accuracy, consistency, uniqueness, and integrity.
• Perform record-level and field-level data comparisons between source and target systems.
• Identify data discrepancies, investigate root causes, and coordinate with development/data engineering teams for resolution.
• Design reusable validation utilities and Python frameworks to improve testing efficiency.
• Automate repetitive data validation and reconciliation processes using Python.
• Validate large datasets efficiently using Python libraries such as **Pandas, NumPy, ** or similar tools.
• Prepare validation reports, defect reports, and execution summaries.
• Track defects and coordinate with technical teams through resolution and retesting.
• Review team members' validation scripts, test cases, and execution results.
• Establish best practices, coding standards, and validation processes for the team.
• Monitor validation progress, risks, dependencies, and deliverables.
• Provide regular status updates to project managers and stakeholders.
• Support root-cause analysis of data quality and migration issues.
• Ensure validation activities are completed within agreed timelines and quality standards.
Required Technical Skills
Python
• Strong hands-on experience with Python.
• Experience developing data validation and reconciliation scripts.
• Good knowledge of Pandas and NumPy.
• Experience working with large datasets.
• Ability to build reusable validation utilities/frameworks.
• Knowledge of exception handling, logging, file processing, and reporting in Python.
SQL & Database Validation
• Strong SQL skills.
• Experience validating data across different databases/systems.
• Experience with source-to-target data validation.
Data Validation
• Data completeness validation.
• Data accuracy validation.
• Data consistency validation.
• Data integrity validation.
• Duplicate and uniqueness checks.
• Null/mandatory field validation.
• Data type and format validation.
• Record count reconciliation.
• Field-level and record-level comparison.
• Source-to-target reconciliation.
• ETL/data migration validation.
Leadership Responsibilities
• Lead and coordinate a team of 3 members.
• Assign validation activities based on project priorities and team capabilities.
• Review and approve test scenarios, test cases, and validation scripts.
• Conduct regular team reviews and track individual/team progress.
• Mentor team members on Python, SQL, and data validation practices.
• Resolve technical blockers and escalate project risks when required.
• Ensure consistent quality and execution standards across the team.
• Coordinate with developers, data engineers, QA teams, business analysts, and project stakeholders.
Preferred Skills
• Experience with data migration or ETL validation projects.
• Experience working with cloud-based data platforms.
• Knowledge of REST APIs and API data validation.
• Experience working with CSV, Excel, JSON, XML, and other data formats.
• Experience with Git/GitHub or similar version-control systems.
• Knowledge of CI/CD and automated validation execution.
• Experience with PyTest or other Python testing frameworks.
• Experience generating automated validation/reconciliation reports.
• Experience working in Agile/Scrum environments.
Key Deliverables
The Data Validation Lead will be responsible for:
1. Data Validation Strategy and Approach
2. Validation Test Scenarios and Test Cases
3. Python Validation Scripts/Frameworks
4. Source-to-Target Reconciliation
5. Data Quality Reports
6. Defect/Discrepancy Reports
7. Validation Execution Reports
8. Root Cause Analysis
9. Team Progress and Status Reports
10. Final Validation Sign-off/Recommendation
Behavioral & Leadership Competencies
• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder-management skills.
• Strong ownership and accountability.
• Ability to work independently and lead a small technical team.
• Ability to troubleshoot complex data issues.
• Good documentation and reporting skills.
• Ability to manage multiple validation activities and priorities.
• Strong attention to detail and data accuracy.
Education
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.

Work arrangement
No