We are seeking an experienced Senior Data Quality Engineer to ensure the accuracy, completeness, consistency, and reliability of data across our pipelines and systems. In this role, you will design and maintain robust validation frameworks, collaborate with cross-functional teams, and play a key part in driving data quality standards within enterprise-wide data and analytics initiatives.
Responsibilities
- Ensure data accuracy, completeness, consistency, and reliability across data pipelines and systems
- Build and maintain data validation frameworks and automated checks
- Identify and resolve data quality issues at source or in transit
- Monitor, profile, and cleanse large datasets to maintain high data integrity
- Collaborate closely with data engineers, analysts, and business stakeholders to define and enforce data quality standards
- Contribute to enterprise-wide data and analytics initiatives by establishing best practices for data governance and quality
- Develop reports and dashboards to track data quality metrics and trends
- Investigate root causes of data anomalies and implement long-term remediation strategies
Requirements
- 3+ years of experience in a data quality, data engineering, or related role
- Expertise in Data Quality methodologies, frameworks, and tooling
- Proficiency in Data Analysis and working with large, complex datasets
- Background in contributing to enterprise-wide data and analytics initiatives
- Skills in Databricks and related big data processing platforms
- Familiarity with Microsoft Azure and cloud-based data services
- Capability to collaborate effectively with data engineers, analysts, and business stakeholders
- Understanding of data profiling, cleansing, and monitoring best practices
- Excellent written and verbal communication skills in English (C1 level)