Data Quality Analyst (The Data Integrity Champion)
Tech Stack
Job Description
Are you passionate about ensuring data accuracy, consistency, and reliability?
Do you have a meticulous eye for detail and a talent for identifying data discrepancies?
If you’re ready to take on the challenge of safeguarding data quality, our client has the ideal role for you.
We’re looking for a Data Quality Analyst (aka The Data Integrity Champion) to monitor, validate, and improve data across the organization, ensuring that our data assets are trustworthy and ready for strategic use.As a Data Quality Analyst at our client, you’ll work with data engineers, analysts, and business stakeholders to develop and maintain data quality standards.
Your role will be critical in ensuring that data used for reporting, analytics, and decision-making is accurate, complete, and timely.Key Responsibilities: Establish and Maintain Data Quality Standards: Define data quality metrics, standards, and KPIs to assess data health.
You’ll implement frameworks to monitor and maintain data accuracy, consistency, completeness, and reliability.
Perform Data Validation and Cleansing: Develop processes to validate and cleanse data from various sources, identifying and correcting errors or inconsistencies.
You’ll work with data engineering teams to automate data validation and improve data integrity.
Conduct Root Cause Analysis on Data Issues: Investigate and resolve data quality issues by performing root cause analysis.
You’ll recommend solutions to prevent data errors and work with teams to implement preventive measures.
Collaborate on Data Governance Initiatives: Partner with data governance and compliance teams to establish data policies and standards.
You’ll ensure that data quality processes align with regulatory requirements and internal standards.
Develop and Run Data Quality Reports: Create reports that assess data quality across datasets, highlighting trends, anomalies, and areas for improvement.
You’ll provide actionable insights to stakeholders to enhance data quality.
Provide Training and Support on Data Quality Best Practices: Educate teams on data quality best practices and promote a culture of data stewardship.
You’ll develop training materials and conduct workshops to empower data users.
Monitor and Optimize Data Quality Tools and Processes: Use and optimize data quality tools (e.g., Informatica, Talend, Trifacta) to streamline data quality checks and validations.
You’ll keep up-to-date with new tools and techniques to improve data quality processes.