Job Summary:

We are looking for a detail-oriented Data Quality Engineer to join our data team. The ideal candidate will be responsible for ensuring the accuracy, completeness, consistency, and reliability of data across our systems. You will work closely with data engineers, analysts, and business stakeholders to implement and maintain data quality frameworks and help drive data-driven decisions.

Key Responsibilities:

• Develop and implement data quality strategies, standards, and processes.
• Design, build, and automate data quality checks, validation scripts, and dashboards.
• Identify, document, and resolve data quality issues across data pipelines and datasets.
• Collaborate with data engineers to integrate data quality checks into ETL/ELT workflows.
• Maintain metadata and data lineage documentation.
• Monitor data pipelines for failures, anomalies, or inconsistencies.
• Communicate data issues and impacts to technical and non-technical stakeholders.
• Support root cause analysis and continuous improvement of data quality processes.

Required Skills & Qualifications:

• Bachelor’s degree in Computer Science, Information Systems, or a related field.
• 5+ years of experience in a Data Quality or Data Engineering role.
• Strong SQL skills and experience with data profiling and validation.
• Experience with data quality tools (e.g., Informatica DQ, Talend DQ, Great Expectations, Deequ).
• Familiarity with ETL tools and data platforms (e.g., Snowflake, BigQuery, Azure Data Factory, etc.).
• Understanding of data governance, master data management (MDM), and metadata management.
• Excellent problem-solving skills and attention to detail.

Preferred Qualifications:

• Experience with Python or other scripting languages.
• Knowledge of data visualization tools (e.g., Power BI, Tableau) for reporting data quality metrics.
• Familiarity with cloud platforms like AWS, Azure, or GCP.