Data Quality Engineer

Job Summary

We are looking for a highly experienced Data Quality Engineer with a strong background in Data Engineering and enterprise-scale data quality initiatives. The ideal candidate will have 10+ years of experience designing, building, and maintaining robust data pipelines and implementing comprehensive data quality frameworks across large data ecosystems.

This role requires excellent communication and stakeholder management skills, as the candidate will work closely with business teams, data architects, analysts, and engineering teams to ensure high standards of data accuracy, consistency, completeness, and reliability.

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
• Implement and manage enterprise data quality frameworks, rules, validations, and monitoring processes.
• Perform data profiling, cleansing, reconciliation, and anomaly detection across multiple data sources.
• Define and enforce data quality standards, governance policies, and best practices.
• Collaborate with cross-functional teams to identify data issues and drive resolution strategies.
• Develop automated data quality checks and reporting dashboards.
• Monitor data integrity, accuracy, timeliness, and completeness across systems.
• Work with large-scale structured and unstructured datasets in cloud and on-prem environments.
• Support root cause analysis for data discrepancies and production incidents.
• Participate in architecture discussions and recommend improvements for data reliability and scalability.
• Create technical documentation, SOPs, and data quality metrics reports for leadership and stakeholders.
• Mentor junior engineers and contribute to overall data engineering best practices.

• 10+ years of experience in Data Engineering and Data Quality Engineering.
• Strong expertise in SQL and data querying techniques.
• Hands‑on experience with ETL/ELT tools and data pipeline development.
• Strong understanding of data quality concepts including:
  • Data validation
  • Data profiling
  • Data reconciliation
  • Data governance
  • Metadata management
  • Data lineage
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Proficiency in Python, Spark, or Scala for data processing.
• Experience working with modern data platforms such as Snowflake, Databricks, Redshift, Big Query, etc.
• Hands‑on experience with data quality tools/frameworks such as:
  • Great Expectations
  • Informatica Data Quality
  • Talend
  • Collibra
  • Monte Carlo
  • Soda
• Strong understanding of database technologies (SQL & No
  
  SQL).
• Experience with CI/CD and Dev Ops practices for data platforms.
• Excellent analytical and problem‑solving abilities.
• Exceptional verbal and written communication skills.
• Ability to interact confidently with technical and business stakeholders.

• Experience in enterprise data governance programs.
• Knowledge of Master Data Management (MDM).
• Exposure to real‑time/streaming data quality monitoring.
• Certifications in cloud/data engineering technologies are a plus.

• Excellent communication and presentation skills.
• Strong stakeholder management capability.
• Self‑driven and proactive mindset.
• Strong collaboration and leadership abilities.
• Ability to work in a fast‑paced, dynamic environment.

• Experience in Agile/Scrum environments.
• Experience with Airflow or orchestration tools.
• Exposure to AI/ML data validation pipelines.