Data Quality Jobs (NOW HIRING)

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Job Description The Data Quality Manager is key in proactively ensuring that data quality is maintained across the enterprise, and as a result enables the Analytics Team to deliver relevant and accurate models and insights. This role acts as the bridge between governance policy and technical implementation, ensuring that critical data quality issues are detected, reported, and resolved before they impact business KPIs.

DUTIES AND RESPONSIBILITIES:

• Establish data quality objectives aligned with Data Governance Policies

• Devises and executes proper data collection procedures, policies, guidelines including data cleaning, standardization, and analysis

• Define, Track and Manage Data Quality KPIs across the enterprise

• Implement controls and compliance metrics to reduce data issues and improve data quality

• Maintain and operationalize data quality dashboards: Oversee the overall presentation of the Data Quality Index, ensuring stakeholders have a real-time view of data health.

• Enhance and operationalize data quality checks: Lead the technical implementation of DQ checks, ensuring they are robust, scalable, and integrated into the data pipeline.

• Apply best practices for data engineering: Utilize engineering standards (CI/CD, version control) when implementing DQ checks and introduce advanced methods such as automated anomaly detection.

• Collaborates with reporting, analytics, and operational segments to ensure data quality standards are met, errors and root causes identified

• Identify, prioritize and lead Enterprise-wide data cleansing initiatives to deliver substantial improvements in data quality across the enterprise

• Plan, manage and deliver communication about the data cleanse activity to the key stakeholders throughout the process.

• Manage project risks and issues and manage stakeholder's expectations on initiatives started

• Align data quality operations with strategic business objectives by prioritizing checks on data assets that feed Core KPIs.

KPIs:

• Data Quality Index (DQI): Assess the overall quality of data across the enterprise, considering factors such as accuracy, completeness, consistency, and timeliness.

• Data Issue Resolution Time: Monitor the time taken to identify and resolve data quality issues reported by various stakeholders.

• Compliance with Data Governance Policies: Ensure adherence to established data governance policies and procedures, including alignment of data quality objectives with governance policies.

• Stakeholder Satisfaction:Measure stakeholder satisfaction with data quality improvements and initiatives through regular surveys or feedback sessions.

TOP 3-5 DELIVERABLES:

• Data Quality Objectives: Establish and communicate data quality objectives aligned with Data Governance Policies, ensuring that they are clearly defined, measurable, and achievable.

• Automated Data Quality Check Suite: A robust library of SQL/DBT-based checks including anomaly detection.

• Incident Impact Reports: Documentation linking DQ issues to specific Business KPI impacts.

• Data Issue Resolution Framework: Operationalized workflow for fixing detected errors.

• Data Quality KPI Management: Define, track, and manage Data Quality Key Performance Indicators (KPIs) across the enterprise, monitoring data quality metrics and performance against established benchmarks.

HIRING REQUIREMENTS:

Work Experience

• 6+ years of experience in working with data management teams

• 5-6 years of experience with implementing or managing enterprise-scale data warehouse or data management projects

• 3+ years of experience managing people or leading project teams

• 3+ years of experience with data warehouse, MDM, and data integration initiatives

Level of Knowledge

• Bachelor's Degree in Computer Science, Computer Engineering, Information Systems or related degree

• Certification in relevant database and business intelligence technologies helpful

• Strong SQL knowledge

• Deep understanding of the architecture discipline, processes, concepts, and best practice

• Strong understanding of data tools (cleansing, master data management, metadata, etc.) and data quality policies and procedures

• Meticulous attention to detail with an overall passion for the discipline of Project Management

• Ability to understand key business drivers and how data quality affects business KPIs.

• Deep understanding of data profiling, cleansing, and metadata management.

• Familiarity with anomaly detection algorithms and statistical monitoring.

Equal Opportunity Employer
Globe's hiring process promotes equal opportunity to applicants, Any form of discrimination is not tolerated throughout the entire employee lifecycle, including the hiring process such as in posting vacancies, selecting, and interviewing applicants.
Globe's Diversity, Equity and Inclusion Policy Commitment can be accessed here

Make Your Passion Part of Your Profession. Attracting the best and brightest Talents is pivotal to our success. If you are ready to share our purpose of Creating a Globe of Good, explore opportunities with us.