We are seeking a Data Quality Analyst for a 6-month contract, with potential for extension, to join a specialized SWAT team focused on resolving data quality challenges and centralizing data responsibilities within the organization. In this role, you will play a critical part in ensuring data accuracy, integrity, and reliability for business decision-making. You will be responsible for identifying, addressing, and preventing data inconsistencies while leveraging analytical tools and methodologies. Collaboration with various teams is essential to enhance data quality across the organization, utilizing tools like SQL, Tableau, Power BI, and data quality management systems.

Key Responsibilities:

Data Quality Management:

• Define and enforce data quality standards across multiple data domains.
• Conduct data quality assessments and audits to identify and resolve inconsistencies, inaccuracies, and data gaps.
• Collaborate with data owners and stakeholders to establish relevant data quality metrics and KPIs.
• Monitor and report on data quality metrics, ensuring ongoing improvements and transparency.
• Offer support and guidance on best practices for data quality management.
• Develop data quality dashboards and reports to facilitate continuous monitoring and analysis.
• Oversee the resolution of all data quality issues, ensuring timely remediation.

Data Profiling and Analysis:

• Perform data profiling to identify patterns, anomalies, and trends that impact data quality.
• Collaborate with data owners, users, and stakeholders to understand data requirements and improve data quality.
• Conduct root cause analysis to identify underlying issues and implement corrective actions.
• Develop and maintain data cleansing routines to enhance the overall quality and integrity of datasets.
• Analyze large datasets to identify and address quality issues that affect decision-making and business processes.

Collaboration and Communication:

• Work closely with Data Teams, Operational Teams, business analysts, and other key stakeholders to foster a culture of data quality management.
• Effectively communicate findings, recommendations, and data quality status to both technical and non-technical audiences.
• Act as a liaison between business teams and technical teams to ensure that data is accurate, complete, and suitable for business analysis.

Continuous Improvement:

• Stay up-to-date with the latest industry trends and emerging technologies related to data governance, data quality management, and data platforms.
• Identify areas for process improvement within the organization’s data management practices, and propose actionable enhancements.
• Propose and implement best practices in data quality that align with industry standards