About The Role

We are looking for a motivated, analytical, and detail-oriented Remote Data Quality Analyst to join our growing data team. This is an exciting opportunity for someone who is passionate about ensuring data accuracy, integrity, consistency, and reliability while supporting data-driven decision-making across the organization.

As a Data Quality Analyst, you will play a critical role in monitoring, validating, and improving the quality of enterprise data. You will work closely with data engineers, business analysts, data scientists, product teams, and business stakeholders to identify data quality issues, investigate root causes, and implement solutions that enhance the reliability of data assets.

You will be responsible for profiling datasets, performing quality assessments, developing validation processes, monitoring key data quality metrics, and supporting continuous improvements in data governance practices. This role requires strong analytical skills, exceptional attention to detail, and the ability to work with large datasets while maintaining high standards of accuracy.

We value collaboration, curiosity, continuous improvement, and a commitment to delivering trustworthy data that empowers better business decisions. You'll gain hands-on experience with modern data quality tools, governance frameworks, and enterprise data management practices while working in a collaborative remote environment.

Key Responsibilities

Data Quality Monitoring

• Monitor data quality across multiple databases, systems, and business applications.

• Perform regular data profiling to identify inconsistencies, duplicates, missing values, and anomalies.

• Validate data accuracy, completeness, consistency, timeliness, and integrity across various data sources.

• Analyze datasets to detect quality issues that may impact reporting, analytics, or business operations.

• Develop and maintain data quality scorecards, dashboards, and performance metrics.

• Ensure data complies with established quality standards and governance policies.

Data Validation & Analysis

• Perform detailed validation of incoming and existing datasets using predefined business rules.

• Investigate data discrepancies and identify root causes of quality issues.

• Execute data reconciliation between multiple systems to ensure consistency.

• Analyze trends in data quality and recommend corrective actions.

• Validate ETL processes and data transformation outputs for accuracy.

• Support testing and validation activities during system implementations and data migrations.

Quality Assurance

• Develop and execute data quality checks and validation procedures.

• Create automated and manual processes for identifying data quality issues.

• Review data correction activities and verify successful resolution.

• Document data quality findings, root cause analyses, and remediation plans.

• Collaborate with technical teams to implement preventive quality controls.

• Monitor ongoing improvements and measure the effectiveness of corrective actions.

Collaboration

• Partner with Data Engineers to improve data pipelines and validation processes.

• Work closely with Business Analysts to understand business rules and data requirements.

• Collaborate with Product Managers and stakeholders to prioritize data quality initiatives.

• Support Data Governance teams in maintaining data standards and policies.

• Communicate findings, recommendations, and progress to technical and non-technical stakeholders.

• Participate in project planning, data quality reviews, and cross-functional meetings.

Documentation & Governance

• Maintain documentation for data quality rules, validation procedures, and reporting standards.

• Assist in developing and updating data governance documentation.

• Create standard operating procedures for data quality management.

• Support metadata management and data lineage documentation.

• Ensure compliance with internal policies and regulatory data requirements.

• Maintain detailed records of quality assessments and issue resolution activities.

Continuous Improvement

• Identify opportunities to automate repetitive data quality processes.

• Recommend improvements to data collection, validation, and reporting workflows.

• Participate in process optimization initiatives that improve overall data reliability.

• Stay informed about emerging data quality tools, technologies, and best practices.

• Contribute to continuous improvement initiatives across the data management lifecycle.

Required Qualifications

• 2–4 years of professional experience in data quality, data analysis, business intelligence, data governance, or a related field.

• Strong understanding of data quality principles, including accuracy, completeness, consistency, validity, and integrity.

• Experience analyzing large datasets using SQL.

• Proficiency in Microsoft Excel, including advanced functions, PivotTables, and data analysis tools.

• Experience working with relational databases and data validation techniques.

• Strong analytical, critical thinking, and problem-solving skills.

• Excellent attention to detail and organizational abilities.

• Experience documenting data quality issues and remediation efforts.

• Strong written and verbal communication skills.

• Ability to manage multiple priorities in a remote, collaborative environment.

Nice to Have

• Experience with data quality tools such as Informatica Data Quality, Talend, Ataccama, Collibra, Great Expectations, or similar platforms.

• Knowledge of data governance frameworks and master data management (MDM).

• Experience working with ETL processes and data integration pipelines.

• Familiarity with business intelligence tools such as Power BI, Tableau, or Looker.

• Basic knowledge of Python or R for data analysis and automation.

• Experience working with cloud data platforms such as AWS, Azure, or Google Cloud Platform.

• Understanding of data warehousing concepts and dimensional modeling.

• Familiarity with version control systems such as Git.

• Experience working in Agile or Scrum environments.

• Knowledge of data privacy regulations, including GDPR, CCPA, or similar compliance standards.

• Experience with API data validation and integration testing.

• Bachelor's degree in Computer Science, Information Systems, Data Analytics, Statistics, Mathematics, or a related field (preferred but not required).

What You'll Gain

• Hands-on experience working with enterprise-scale data systems and modern data platforms.

• Opportunities to collaborate with experienced data engineers, analysts, and business stakeholders.

• Exposure to data governance, business intelligence, and advanced analytics initiatives.

• Professional development through training on modern data quality tools and best practices.

• A collaborative, inclusive, and supportive remote work environment.

• Opportunities to contribute to strategic data initiatives that drive business performance.

• Career growth within Data Analytics, Data Engineering, Business Intelligence, and Data Governance.

• Experience improving the quality and reliability of data that supports key organizational decisions.

What We're Looking For

We're seeking someone who enjoys solving complex data problems, improving data accuracy, and ensuring organizations can trust the information they use every day. The ideal candidate is analytical, detail-oriented, proactive, and committed to continuous improvement. You should be comfortable working with large datasets, collaborating across teams, and communicating findings clearly to both technical and business stakeholders. If you're passionate about data quality and want to help build reliable, high-performing data ecosystems, we'd love to hear from you.