Job Description

We are looking for a QA Data Engineer who can validate, test, and support data pipelines using ETL tools, SQL, and Python. The role focuses on data accuracy, pipeline testing, and quality checks across large datasets.

 Responsibilities

 

• Validate ETL pipelines and data flows using Azure Data Factory or other ETL tools

• Write Python scripts for data checks, automation, and validation

• Perform data reconciliation between source and target systems

• Execute data profiling, data quality checks, and rule-based validations

• Review and test data models, schemas, and transformations

• Support data migration testing for SAP, Oracle, SQL, or CRM systems

• Work with engineering teams to identify and resolve data issues

• Document test scenarios, validations, and test results

 

Must-Have Skills

 

• Strong SQL (joins, aggregations, transformations, validations)

• Hands-on ETL experience (ADF / SSIS / Informatica / Talend)

• Good Python scripting for data validation & automation

• Experience performing data quality testing (S2T, reconciliation, profiling)

• Understanding of data models (fact, dimension, schema structures)

• Experience working with SQL Server / Oracle / MySQL / SAP databases

 

Nice-to-Have Skills

 

• Azure cloud knowledge

• Shell/Bash scripting

• Exposure to big data tools (Hadoop, Databricks)

 

Soft Skills

 

• Strong analytical mindset

• Good communication

• Open to feedback and collaborative work style

• Ability to work in fast-paced engineering teams

 

Qualification

• Bachelor’s degree in Computer Science, IT, Engineering, or related field
• Relevant certifications in Azure / ETL / Data Engineering (preferred)