Senior Data Steward - Data Quality & Governance (4-8 yrs)

Job Description :

The Senior Data Steward will play a pivotal role in overseeing the governance, quality, and management of the organization's data. They will be responsible for maintaining data accuracy, integrity, and compliance across the data platform while ensuring alignment with business objectives. This role requires a seasoned data management professional with at least 7-9 years of experience in data governance, data engineering, and leadership, and a strong technical proficiency in data engineering and governance tools. The Senior Data Steward will lead the collaboration between IT, data engineering, and business teams to optimize data processes and workflows.

Key Responsibilities :

- Data Governance Framework Management : Lead the implementation and enforcement of data governance policies and procedures to ensure compliance with internal standards and regulatory requirements.

- Data Platform Oversight : Oversee the operational management of data platforms, ensuring data is properly structured, managed, and secured.

- Data Quality Assurance : Implement and manage data quality controls to ensure that the data used across business functions is accurate, complete, and reliable.

- Collaboration Across Teams : Act as the primary point of contact between IT, data engineering teams, and business units to ensure alignment on data-related initiatives.

- Data Engineering Support : Provide technical guidance and expertise to data engineering teams, ensuring proper architecture, integration, and performance of data pipelines.

- Stakeholder Engagement : Work closely with business leaders to understand data needs and define data requirements to meet strategic objectives.

- Data Stewardship Leadership : Lead the efforts to assign, track, and monitor data stewardship roles, ensuring accountability and ownership of data across the organization.

- Tool and Technology Management : Ensure the effective use of data governance tools, data engineering tools, and other related technologies to enhance data management processes.

- Process Improvement : Drive continuous improvement initiatives for data management processes, ensuring efficiency and scalability across teams and systems.

- Metadata Management : Manage metadata to ensure proper tagging, classification, and documentation of data across various platforms, making it easily accessible and understandable for users.

- Compliance and Risk Management : Identify and mitigate data-related risks, ensuring adherence to data privacy laws, security protocols, and compliance regulations.

- Data Lifecycle Management : Oversee the entire data lifecycle, from data creation and storage to archiving and disposal, ensuring processes are well-defined and followed.

- Data Integration : Work with the data engineering team to design and implement integration strategies that allow for seamless data flow across systems.

- Performance Metrics and Reporting : Develop and track key performance indicators (KPIs) to measure the effectiveness of data governance and data management practices.

- Data Access Control : Ensure proper data access controls are in place, facilitating secure and authorized access to data while maintaining compliance with security standards.

- Issue Resolution and Escalation : Act as the point of escalation for data-related issues and collaborate with technical teams to troubleshoot and resolve complex data problems.

- Training and Mentorship : Provide guidance and mentorship to junior data stewards and other team members, promoting a culture of data literacy and stewardship across the organization.

- Documentation and Knowledge Management : Ensure that data management processes, procedures, and policies are well-documented and accessible for all stakeholders.

- Change Management : Lead change management initiatives related to data processes, ensuring smooth transitions and minimal disruption to operations.

- Data Governance Audits : Conduct regular data audits to ensure compliance with governance frameworks and identify areas for data quality improvement.

Required Skills and Experience :

- Experience : Minimum of 7-9 years in data management, including at least 5 years in data governance, data quality, and data engineering leadership roles.

- Technical Skills : Strong proficiency with data governance tools (e.g., Collibra, Alation), data engineering tools (e.g., Apache Kafka, Apache Spark, SQL, ETL tools), and data management frameworks.

- Leadership : Experience leading cross-functional teams, managing data processes, and driving strategic data initiatives.

- Knowledge : Expertise in data privacy, compliance regulations

- Collaboration : Proven track record of working effectively with business, IT, and data teams to meet business objectives.

- Communication : Strong verbal and written communication skills, with the ability to present complex data concepts to non-technical stakeholders.

- Problem-Solving : Strong analytical and problem-solving skills to resolve data-related issues and optimize data management processes.