
Salla
Senior Data Quality Engineer
- Permanent
- Medina, Saudi Arabia
- Experience 5 - 10 yrs
Job expiry date: 12/05/2026
Job overview
Date posted
28/03/2026
Location
Medina, Saudi Arabia
Salary
SAR 20,000 - 30,000 per month
Compensation
Comprehensive package
Job description
The Senior Data Quality Engineer at Salla, a leading e-commerce platform, is responsible for ensuring the accuracy, consistency, and reliability of organizational data pipelines within a hybrid work environment based in Madinah, Saudi Arabia. The role involves defining and implementing data quality frameworks, establishing and monitoring data quality KPIs such as completeness, accuracy, timeliness, and consistency, and driving continuous improvement initiatives across data systems. The position requires hands-on expertise in SQL, ETL tools, data pipelines, and relational databases, along with programming capabilities in Python or R for data validation and automation. Core activities include data profiling, data validation, and data cleansing across multiple systems, writing SQL/ETL tests to detect issues early, building data validation pipelines, implementing real-time data flow validation, and automating data cleansing and standardization processes. The engineer is expected to design and maintain data monitoring pipelines, create data quality metrics and dashboards, and set up anomaly detection alerts. Additionally, the role includes leading root cause analysis and corrective action planning for recurring data issues, ensuring adherence to best practices in data quality assurance, and staying updated with emerging industry trends. The position requires collaboration with data engineers, analysts, and business stakeholders to troubleshoot issues, enhance data processes, and ensure alignment with business objectives. A solid understanding of data modeling, metadata management, and master data concepts is essential, along with experience in data quality tools and automated QA/data validation pipeline design.
Required skills
Key responsibilities
- Design, implement, and maintain data quality frameworks, best practices, and governance processes to ensure the accuracy, consistency, and reliability of data pipelines across multiple systems and databases
- Define, track, and continuously monitor data quality KPIs including completeness, accuracy, timeliness, and consistency while developing actionable insights to improve overall data integrity
- Perform comprehensive data profiling, data validation, and data cleansing activities, ensuring high-quality data standards across all integrated systems and databases
- Develop and execute SQL and ETL tests to identify and resolve data issues early in the pipeline lifecycle, ensuring robust and reliable data processing workflows
- Build, deploy, and maintain automated data validation pipelines and data monitoring pipelines, including real-time validation of data flows across multiple systems
- Create and maintain data quality metrics, dashboards, and anomaly detection alerts to proactively identify inconsistencies and performance issues within datasets
- Lead root cause analysis initiatives and implement corrective action plans to address recurring data quality issues, ensuring long-term data reliability and process improvement
- Collaborate cross-functionally with data engineers, data analysts, and business stakeholders to troubleshoot data issues, improve data processes, and align data quality initiatives with organizational objectives
Experience & skills
- Demonstrate a minimum of 5+ years of experience in data quality assurance or a similar role with proven expertise in managing and improving data quality across complex data environments
- Exhibit strong proficiency in SQL and hands-on experience with relational databases, ensuring efficient querying, validation, and troubleshooting of large datasets
- Show advanced programming capabilities in Python or R or other data-focused languages for data validation, automation, and pipeline development
- Possess practical experience with ETL tools and data pipelines, including designing, implementing, and maintaining scalable and reliable data workflows
- Demonstrate solid understanding of data modeling, metadata management, and master data management concepts to support structured and governed data environments
- Provide experience with data quality tools and software, including the ability to design and implement automated QA and data validation pipelines
- Hold a Bachelor’s degree in Computer Science, Data Management, Information Systems, or a related field, with knowledge of e-commerce or retail industry considered an advantage
- Exhibit capability to work cross-functionally with technical and business teams, contributing to data quality initiatives, troubleshooting processes, and continuous improvement strategies