Top 20 C2C Job Opportunity -Informatica Data Quality Developer-Columbus, OH Quick apply

The role of a Data Quality Developer involves ensuring the accuracy, consistency, and reliability of data within an organization. Here are the top 10 common job responsibilities for a Data Quality Developer:

1. Data Quality Assessment:
   • Evaluate the quality of existing data sets by analyzing data accuracy, completeness, consistency, and timeliness.
2. Data Profiling:
   • Conduct data profiling activities to understand the structure, patterns, and quality of data across different sources.
3. Data Cleansing:
   • Develop and implement data cleansing processes to correct or remove inaccuracies, inconsistencies, and errors in the data.
4. Data Standardization:
   • Implement data standardization techniques to ensure that data adheres to defined formats, units, and conventions.
5. Data Validation:
   • Create and apply validation rules to identify and rectify data anomalies, ensuring data meets predefined standards.
6. Data Enrichment:
   • Implement strategies to enhance the quality of data by enriching it with additional information from external sources.

1. Data Monitoring:
   • Set up monitoring processes to continuously assess and track the quality of incoming and existing data.
2. Collaboration with Data Stakeholders:
   • Collaborate with data owners, data stewards, and other stakeholders to understand data quality requirements and expectations.
3. Data Quality Metrics Reporting:
   • Develop and generate reports on data quality metrics, providing insights into the overall health of the organization’s data.
4. Data Governance Implementation:
   • Work on the implementation and enforcement of data governance policies and procedures to maintain data quality standards.
5. Root Cause Analysis:
   • Conduct root cause analysis to identify the sources of data quality issues and implement preventive measures.
6. Quality Improvement Recommendations:
   • Provide recommendations for improving data quality processes, tools, and standards based on continuous monitoring and assessment.
7. Automation of Data Quality Checks:
   • Automate data quality checks and validation processes to ensure real-time monitoring and proactive identification of issues.
8. Collaboration with IT Teams:
   • Collaborate with IT teams, including database administrators, developers, and data engineers, to integrate data quality processes into the overall data management strategy.
9. Documentation:
   • Maintain documentation for data quality processes, rules, and standards to ensure clarity and consistency.

Data Quality Developers play a critical role in maintaining a high level of data accuracy and reliability within an organization. Their responsibilities involve implementing strategies, processes, and tools to address and prevent data quality issues across the entire data lifecycle.