Senior Data Quality Engineer

symplr; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

symplr is seeking a Senior Data Quality Engineer with 5+ years of experience to drive testing initiatives for our Data Platform in Bengaluru. You will focus on ETL testing, data validation, and ensuring data integrity across AWS-based pipelines and Power BI reports.

The role requires expertise in test automation, scripting, SQL, and collaborating with data engineers to uphold data quality for analytics and reporting teams.

Qualifications

• 5+ years in data quality engineering, data testing, or related fields.
• Strong hands-on experience with ETL testing and data validation techniques.
• Experience working with AWS data services and Power BI for validation of data models.
• Familiarity with test automation and scripting to build regression suites.

Responsibilities

• Contribute to development and execution of data quality strategies.
• Web UI/tools testing: create test cases and scenarios.
• Load testing to assess high data volumes.
• ETL testing: test case development, data validation, transformation accuracy, end-to-end pipeline testing, performance testing.
• AWS Data Pipeline Monitoring: support monitoring of AWS-based pipelines for data accuracy and reliability.
• Power BI Reports: validate data lineage and report outputs against sources.
• Collaborate with data engineers, analysts and stakeholders to resolve data quality issues.
• Maintain documentation of testing procedures, results, and quality metrics.

Skills

ETL testing

Data validation

SQL

Power BI

Python scripting

AWS data services

Agile / Scrum

Data governance

Data observability

Tools

AWS Glue

S3

Athena

MSK

SQS

Lambda

Step Functions

Power BI

Job description

Overview

symplr is seeking a highly skilled and motivated Senior Data Quality Engineer with 5+ years of experience to execute testing initiatives for our robust Data Platform. This role is instrumental in maintaining the integrity, reliability, and performance of our data systems. The ideal candidate will bring strong expertise in ETL testing, data validation, AWS-based data workflows, and Power BI reports, with a solid foundation in Test Automation and scripting. Readiness on learning/understanding new tools.

Duties & Responsibilities

• Contribute to the development and execution of data quality strategies and best practices to support the organization’s data initiatives.
• Web UI/tools testing: Create testcases and scenarios based on features and requirements.
• Load Testing: Ability to test the system with high volume of data
• ETL Testing: Design and perform thorough ETL tests, including test case development, data validation, transformation accuracy, end-to-end pipeline testing, and performance testing.
• AWS Data Pipeline Monitoring: Support the monitoring of AWS-based pipelines using services like S3, SQS, Lambda etc. to ensure workflows, data accuracy, completeness, and reliability.
• Power BI Reports: Ensure data accuracy and consistency in Power BI reports by validating data lineage, transformation logic, and report outputs against source systems.
• Collaboration: Work alongside data engineers, analysts, and business stakeholders to understand data flows and resolve data quality issues.
• Documentation: Maintain clear and detailed documentation of testing procedures, test results, and quality metrics in addition to product/processes workflows.

Skills Required

• 5+ years of experience in data quality engineering, data testing, or related fields.
• Strong hands-on experience with ETL testing and data validation techniques.
• Experience working with AWS data services, including Glue, S3, Athena, MSK, SQS, Lambda, Step Functions, etc.
• Experience in building Automated regression test suites
• Proficiency in writing SQL and basics of any OOP languages
• Experience validating data using Power BI reports, including understanding of data models and report logic.
• Familiarity with test management tools such as Azure DevOps, Zephyr, or equivalent.
• Validated ingestion and transformation logic for large-scale batch and real-time data workflows.
• Experience working in Agile environments (Scrum/Kanban).
• Exposure to data governance principles or data observability tools is a plus.
• Strong problem-solving skills and a proactive approach to identifying data quality issues.
• Ensured data availability and integrity for analytics & reporting teams.
• Good communication skills and the ability to work effectively with cross-functional teams.
• Continuous learning mindset and willingness to adapt to new technologies and techniques.

Good to have:

• Automation & Scripting: Develop Python-based scripts to automate data quality checks and validation processes.
• Experience in Conducting root-cause analysis for data anomalies, improving issue resolution time.
• Understanding of Data warehouse tools like Redshift