Data Management Specialist

Roles and responsibilities

Establishing and enforcing data governance policies to ensure data quality, security, compliance, classification, and accessibility across the organization. They develop governance frameworks, align data practices with regulations like PDPL, NDMO, etc., and collaborate with IT, legal, and business teams to implement best practices.
The role includes managing data quality, maintaining an enterprise data catalog for organized and discoverable data assets, and implementing data classification strategies to protect sensitive information.
Ensure proper data integrity, access controls, and risk mitigation, to enable a data-driven culture and regulatory compliance.
ensure that data is treated as a strategic asset, supporting business objectives, operational efficiency, and decision-making while maintaining trust in data systems.
Safeguard Data Assets to Ensure data protection, availability, proper classification of sources and systems, and smooth integration within SPL.
Data Governance and Strategy
Data Governance Framework: Develop and implement data governance policies and frameworks to ensure data quality, consistency, and compliance with legal and regulatory standards.
Data Ownership and Stewardship: Define roles and responsibilities for data ownership across the organization to ensure accountability and proper data stewardship.
Data Strategy: Collaborate with leadership to define the organization’s data strategy, aligning it with business objectives and operational needs.
. Data Quality Management
Data Accuracy and Consistency: Establish processes to ensure data is accurate, complete, and consistent across all systems and databases.
Data Cleansing: Implement data cleansing strategies to remove duplicates, correct errors, and improve data integrity.
Quality Control: Develop and monitor metrics for data quality and implement continuous improvement strategies to maintain high standards.
Data Integration and Architecture
Data Integration: Oversee the integration of data from multiple sources, ensuring seamless and accurate data flow between systems (e.g., CRM, ERP, and databases).
Data Architecture Design: Design and optimize data architecture to meet the organization’s needs, including data models, storage solutions, and cloud infrastructure.
ETL Processes: Manage Extract, Transform, Load (ETL) processes to efficiently extract data from various systems, transform it to the desired format, and load it into data storage systems.

Desired candidate profile

Data Management

Data Strategy

Data Governance

Data Science

Information Technology
Database Management
Database Design and Maintenance: Design, implement, and maintain databases that efficiently store and organize data. Ensure databases are optimized for performance, security, and scalability.
Database Security: Ensure the security of data stored in databases by implementing appropriate access controls, encryption methods, and backup procedures.
Database Performance Optimization: Monitor database performance and implement optimization techniques to ensure quick and reliable access to data.
Data Security and Compliance
Data Privacy: Ensure that data management practices adhere to data privacy regulations, such as GDPR, HIPAA, or CCPA, to protect sensitive information.
Compliance Management: Work closely with legal and compliance teams to ensure that the organization’s data management practices are compliant with industry standards and regulations.
Risk Management: Identify data-related risks and develop mitigation strategies to prevent data breaches or loss.
. Data Access and Usage
Data Accessibility: Ensure that data is accessible to authorized users when needed, while maintaining proper security measures and controls.
Data Sharing: Establish guidelines and protocols for securely sharing data across departments, teams, and external partners.
Data Analytics Support: Support data analysts and business intelligence teams by providing clean, accessible data and ensuring data is properly formatted for analysis