Data Quality Engineer | Drive Data Integrity & Insights

Datamatics Technologies LLC; Lahore; On-site; PKR 1,800,000 - 3,200,000; Full time

Job summary

Datamatics Technologies LLC is seeking a Data Quality Engineer to ensure the accuracy, completeness, and reliability of enterprise data assets. The role requires strong SQL skills and hands-on experience with Informatica IDMC/IDQ, Microsoft Fabric Purview, or Databricks.

You will develop data quality rules, perform profiling and validation, and monitor quality metrics. Collaboration with stakeholders and cross-functional teams is essential to drive remediation and data governance improvements.

Qualifications

• 4–5 years of experience in Data Quality, Data Governance, or Data Engineering.
• Strong SQL and data analysis skills.
• Experience with data profiling, validation, reconciliation, and root cause analysis.
• Experience implementing data quality rules, controls, and monitoring processes.
• Hands-on experience with Informatica IDMC/IDQ, Microsoft Fabric Purview, or Databricks.
• Strong problem-solving and stakeholder management skills.

Responsibilities

• Develop and maintain data quality rules, controls, and standards.
• Perform data profiling, validation, and reconciliation activities.
• Monitor data quality metrics and resolve quality issues.
• Conduct root cause analysis and support remediation efforts.
• Collaborate with business and technical teams to improve data quality.

Skills

SQL

Data quality

Data governance

Data engineering

Data profiling

Validation

Reconciliation

Root cause analysis

Stakeholder management

Informatica IDMC/IDQ

Databricks

Microsoft Fabric Purview

Tools

Informatica IDMC/IDQ

Microsoft Fabric Purview

Databricks

Job description

Datamatics Technologies LLC is seeking a Data Quality Engineer to ensure the accuracy, completeness, and reliability of enterprise data assets. The role requires strong SQL skills and hands-on experience with Informatica IDMC/IDQ, Microsoft Fabric Purview, or Databricks.

You will develop data quality rules, perform profiling and validation, and monitor quality metrics. Collaboration with stakeholders and cross-functional teams is essential to drive remediation and data governance improvements.