Data Governance Lead

Description:

• Bachelor's degree in Computer science or equivalent, with minimum 12+Years of relevant experience.
• Strong Experience  of data governance and compliance standards
• Minimum of 5 years of experience in data engineering, data quality management, and data lake implementation.
• Proven experience with Databricks and Azure.
• Strong analytical and problem-solving skills.
• Excellent communication and presentation skills.
• Ability to work effectively in a fast-paced, dynamic environment.

Preferred Skills:

• Experience with other data quality tools and technologies.
• Certification in data management or data quality.
• Familiarity with machine learning and AI techniques.

Responsibilities:

Collaboration & Mitigation:

• Work with business teams and upstream application teams to mitigate data quality issues at the source.
• Collaborate with stakeholders to define and implement new data quality (DQ) business rules.
• Build exception handling and inline data quality processes within Databricks for the entire data lifecycle.

Data Profiling & Rule Definition:

• Perform data profiling to identify data quality issues and opportunities for improvement.
• Work with business stakeholders to define and implement data quality rules and standards.
• Ensure data quality rules are integrated into data processing workflows and monitored for compliance.

Issue Management:

• Implement a robust issue management process to track and remediate data quality-related issues.
• Identify data quality issues proactively by understanding different consumption patterns and implementing checks and balances.
• Monitor data quality and publish regular reports on data health.

Leadership & Collaboration:

• Lead analysts and the daily monitoring team to identify data anomalies.
• Work closely with domain leads and business data stewards in the remediation process.
• Foster a culture of data quality awareness and continuous improvement.

Reporting & Communication:

• Create and present data quality reports to senior management and stakeholders.
• Communicate data quality progress, challenges, and solutions effectively to both technical and non-technical audiences.
• Collaborate with cross-functional teams to ensure data quality standards are met.