Data Automation Tester (SJ-IQ)

SE Mentor Solutions; Ernakulam; Hybrid; INR 700,000 - 1,000,000; Full time

Job summary

SE Mentor Solutions in Kochi is seeking an experienced ETL / Data Automation QA Engineer with 4+ years of hands-on experience validating complex data pipelines, writing advanced SQL, and building scalable test automation using Python and Pytest. You will ensure data accuracy and integrity across data warehouses, support CI/CD integration, and collaborate with Data Engineers and Analytics teams.

This hybrid role requires 2-3 days in the office per week, with final F2F interview at our Kochi

Qualifications

• 4+ years of hands-on experience in Data Quality Assurance, ETL Testing, or Data Automation.
• Strong ability to write advanced SQL queries (window functions, subqueries, joins, performance tuning).
• Proficient in Python and Pytest for data testing scripts.
• Deep understanding of ETL concepts and data warehousing principles (Star/Snowflake schemas).
• Experience with relational databases and cloud data warehouses.

Responsibilities

• Design, execute, and maintain end-to-end test cases for ETL processes and data pipelines.
• Write and optimize SQL queries to audit and validate large datasets across systems.
• Build scalable data testing automation frameworks using Python and Pytest.
• Identify, log, and track data anomalies, schema changes, and pipeline failures with engineers.
• Validate data transformations, business logic, and schema integrity.
• Integrate automated data tests into CI/CD pipelines for continuous data quality.

Skills

Advanced SQL

Python

Pytest

ETL Testing

Data Warehousing

Git

Jira

Tools

PostgreSQL

MySQL

MS SQL

Snowflake

Job description

Job Title: ETL / Data Automation QA Engineer

Experience: 4+ Years

Location: Kochi, Kerala

Work Mode: Hybrid (2-3 days in office / week)

Interview Process: Final Round will be Face-to-Face (F2F) at our Kochi office

About The Role

We are seeking an experienced ETL / Data Automation QA Engineer with 4+ years of hands-on experience in validating complex data pipelines, writing advanced SQL queries, and building scalable test automation frameworks using Python and Pytest. In this role, you will ensure data accuracy, integrity, and performance across large-scale data warehouses and ETL processing layers.

Key Responsibilities

• ETL & Data Testing: Design, execute, and maintain end-to-end test cases for ETL processes, data integration, data pipelines, and data migration projects.
• Complex SQL Validation: Write advanced, highly optimized SQL queries to audit, reconcile, and validate large datasets across source and target systems.
• Automation Engineering: Build and scale data testing automation frameworks using Python and Pytest to automate repetitive data validation and pipeline checks.
• Defect & Data Quality Management: Identify, log, and track data anomalies, schema changes, and pipeline failures, collaborating closely with Data Engineers and Analytics teams.
• Data Verification: Validate data transformations, business logic, null checks, duplicate checks, boundary conditions, and schema integrity.
• CI/CD Integration: Integrate data automated tests into modern CI/CD pipelines to ensure continuous data quality monitoring.

Required Skills & Qualifications

• Experience: Minimum 4+ years in Data Quality Assurance, ETL Testing, or Data Automation.
• Advanced SQL: Expertise in writing complex SQL queries (window functions, subqueries, CTEs, heavy JOINs, performance tuning, and set operations).
• Programming & Frameworks: Strong proficiency in Python and hands-on experience with Pytest for creating data testing scripts.
• ETL & Data Warehousing: Deep understanding of ETL concepts, data warehousing principles (Star/Snowflake schemas), and source-to-target mapping.
• Database Systems: Experience working with relational databases (PostgreSQL, MySQL, MS SQL) or cloud data warehouses (Snowflake, Databricks, Redshift, BigQuery).
• Tools: Proficiency with version control systems (Git) and bug-tracking platforms (Jira).

Nice to Have

• Experience testing big data architectures (Apache Spark, PySpark, AWS S3).
• Familiarity with orchestration tools (Apache Airflow, Prefect).
• Basic exposure to cloud platforms (AWS, Azure, or GCP).

Work Location & Selection Process

Primary Work Location: Kochi (Hybrid work environment).

Selection Process: Technical Screening - Hands-on Coding/SQL Assessment - Final F2F Technical & HR Interview at the Kochi Office.