Senior Data Quality Engineer

Salla, a leading e-commerce platform, is seeking a Senior Data Quality Engineer to ensure the accuracy, consistency, and reliability of our organization’s data pipelines. As a Data Quality Engineer, you will be responsible for defining data quality standards, implementing quality frameworks, monitoring key metrics, and driving continuous improvements. This role requires both technical expertise and strong communication skills to collaborate across teams including data engineering, analytics, and business stakeholders.

Key Responsibilities

• Design, implement, and maintain data quality frameworks and best practices.
• Define and monitor data quality KPIs such as completeness, accuracy, timeliness, and consistency.
• Conduct data profiling, validation, and cleansing across multiple systems and databases.
• Writing SQL/ETL tests to catch issues early
• Building data validation and monitoring pipelines
• Validating data flows in real time across multiple systems
• Collaborating with data engineers, analysts, and business teams to fix root causes
• Creating data quality metrics & dashboards
• Setting up alerts for anomalies
• Automating data cleansing and standardization processes
• Lead root cause analysis and corrective action plans for recurring data issues.
• Stay up-to-date with industry best practices and emerging trends in data quality assurance.
• Bachelor’s degree in Computer Science, Data Management, Information Systems, or a related field.

• Knowledge of e-commerce or retail industry is a plus.
• Ability to work independently and as part of a team.

• Ability to work cross-functionally and influence stakeholders at different levels

Requirements:
• 5+ years of experience in data quality assurance or a similar role.
• Proficiency in SQL and experience with relational databases.
• Strong in Python or R or any other language used for data validation and automation.
• Hands-on experience with ETL tools and data pipelines.
• Solid understanding of data modeling, metadata management, and master data concepts.
• Strong problem-solving, analytical thinking, and communication skills.
• Effective communication skills, both verbal and written.
• Experience with data quality tools and software.
• Proven ability to design and implement automated QA/data validation pipelines.

Benefits:
• Medical Health Insurance
• Performance Bonus
• Other Benefits