ETL Test Engineer – Data Warehouse, SQL, Database Testing & Python

Synechron Technologies Pvt. Ltd._INDIA Company; Bengaluru; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Synechron is seeking an ETL Tester for its Bangalore team to validate data pipelines, transformations, migrations, and loading processes across source to target systems.

The role requires 5–8 years in ETL testing, data warehouse and database testing, with basic Python scripting and experience in SQL, testing tools, and BI reporting validation.

Qualifications

• 5–8 years of experience in ETL testing, data warehouse testing, and database testing.
• Strong SQL skills with complex queries and data validation.
• Basic Python scripting for test automation and data validation.
• Experience with ETL tools such as Informatica, Talend, SSIS, or DataStage.
• Exposure to JIRA, ALM, Azure DevOps for defect tracking.
• Understanding of data pipelines, data quality, and BI reporting validation.

Responsibilities

• Validate ETL workflows, data migrations, and loading across source, staging, warehouse, and target systems.
• Design and execute ETL test cases and data validation scripts.
• Perform database testing with complex SQL queries and validation logic.
• Prepare test plans, strategies, and execution reports.
• Collaborate with developers and data engineers; report defects and support resolution.
• Support testing efforts with Python scripts for data comparison and validation.
• Validate BI reports/dashboards with Power BI or Tableau.

Skills

SQL

Python

Data Validation

ETL Testing

Data Warehouse Testing

Database Testing

Test Automation

JIRA

Azure DevOps

Power BI

Tableau

Education

Bachelor's degree in Computer Science/IT/Engineering

Tools

Informatica

Talend

SSIS

DataStage

JIRA

ALM

Azure DevOps

Power BI

Tableau

Job description

Job Summary

Synechron is seeking an ETL Tester – Data Warehouse, Database Testing and Basic Python for its Bangalore team. The role requires 5–8 years of experience in ETL testing, data warehouse testing, database testing, and basic Python scripting. The successful candidate will validate data pipelines, transformations, migrations, and loading processes to ensure data accuracy, completeness, consistency, and integrity across end-to-end data solutions. This role contributes to business objectives by identifying data issues early, improving confidence in reporting and analytics, and supporting reliable data delivery.

Software Requirements (Required and Preferred)

• Required ETL Testing Tools: Hands-on experience with at least one ETL tool, such as Informatica, Talend, SSIS, DataStage, or a similar platform.


• SQL: Strong experience writing complex queries, joins, subqueries, stored procedures, reconciliation queries, and data validation scripts.


• Python: Basic practical knowledge for scripting, test automation support, data validation, comparison activities, and test utilities.


• Database Testing Tools: Experience using database query and validation tools relevant to the project environment.


• Defect Tracking and Test Management Tools: Experience with JIRA, ALM, Azure DevOps, or equivalent tools.


• Data Warehouse Testing: Experience validating data extraction, transformation, loading, migration, and source-to-target processing.


• Testing Documentation Tools: Experience preparing test plans, test strategies, test cases, test scenarios, test scripts, execution reports, and defect documentation.


• Preferred Agile/Scrum Tools and Practices: Experience working with sprint planning, backlog management, daily stand-ups, reviews, retrospectives, and delivery tracking.


• Cloud Data Platforms: Exposure to cloud-based data platforms, including AWS, Azure, GCP, or equivalent environments.


• BI Reporting Tools: Knowledge of validating reports and dashboards using Power BI, Tableau, or similar business intelligence tools.


• Test Automation Frameworks: Basic understanding of frameworks and utilities used for test automation, data comparison, and regression testing.


• Data Quality Tools: Exposure to tools used for data profiling, data quality monitoring, reconciliation, or data governance.

Overall Responsibilities

Validate ETL workflows, data migrations, data transformations, and data loading processes across source, staging, warehouse, and target systems.

Perform source-to-target data validation and reconciliation to verify data accuracy, completeness, consistency, and integrity.

Design, develop, and execute ETL test cases, test scenarios, test scripts, and test data based on business and technical requirements.

Conduct database testing using complex SQL queries, joins, stored procedures, and validation logic.

Analyze business and technical requirements and prepare test plans, test strategies, traceability records, and execution approaches.

Validate large data volumes and transformation logic across fact tables, dimension tables, star schemas, snowflake schemas, and related data structures.

Perform regression, integration, system, migration, and data quality testing throughout the delivery lifecycle.

Identify, document, prioritize, track, and report defects, and work with development and data engineering teams to support timely resolution.

Use basic Python scripts for test automation support, data validation, data comparison, reconciliation, and repetitive testing activities.

Create and maintain test execution reports, defect reports, test evidence, validation results, and other testing documentation.

Participate in requirement discussions, test planning, defect triage, review meetings, release activities, and post-deployment validation.

Ensure testing activities follow approved quality, security, data handling, and delivery standards.

Support efficient test execution by reusing test assets, automating suitable validation tasks, and considering responsible use of compute, storage, and processing resources.

Technical Skills (By Category)

Programming Languages Essential

Strong SQL skills, including complex queries, joins, subqueries, aggregations, stored procedures, and data validation logic.

Basic Python knowledge for scripting, data comparison, validation, test automation support, and repetitive testing activities.

Ability to interpret transformation logic and validate expected outcomes across ETL processes.

Preferred Additional scripting experience for test utilities, reporting, log analysis, or automation.

Experience using Python libraries for file comparison, data analysis, database connectivity, or test support.

Databases and Data Management Essential

Strong experience in database testing and data warehouse testing.

Experience validating large data volumes across source, staging, warehouse, and target environments.

Understanding of fact tables, dimension tables, star schema, snowflake schema, data marts, and data warehouse layers.

Experience with source-to-target validation, reconciliation, data completeness, transformation accuracy, and data consistency checks.

Ability to analyze data discrepancies and determine whether issues originate from source data, transformation logic, mappings, loading processes, or target structures.

Experience working with relational databases and writing SQL-based validation scripts.

Preferred Exposure to cloud databases, data lakes, data warehouses, or distributed data processing environments.

Knowledge of data profiling, data quality rules, metadata, lineage, and data governance practices.

Experience validating BI reports, dashboards, and analytical datasets.

Cloud Technologies Essential

Ability to perform or support ETL and database testing in the environments used by the assigned project.

Understanding of data movement, connectivity, storage, and validation considerations in enterprise data environments.

Preferred Exposure to AWS, Azure, GCP, or equivalent cloud data platforms.

Experience testing cloud-based ETL pipelines, data warehouses, data lakes, or integration services.

Familiarity with cloud monitoring, logging, access controls, and environment-based test execution.

Frameworks and Libraries Essential

ETL testing experience using Informatica, Talend, SSIS, DataStage, or a similar ETL platform.

Understanding of ETL testing approaches, including workflow validation, transformation testing, data migration testing, load validation, and reconciliation.

Ability to develop reusable SQL and basic Python utilities for data validation and comparison.

Preferred Basic understanding of test automation frameworks.

Exposure to Python libraries or testing utilities used for database connectivity, file comparison, data analysis, and test reporting.

Experience validating BI reports and dashboards using Power BI, Tableau, or similar tools.

Development Tools and Methodologies Essential

5–8 years of experience in ETL testing, data warehouse testing, database testing, or related quality assurance roles.

Experience preparing test plans, test strategies, test cases, test scenarios, test scripts, execution reports, and defect documentation.

Experience with defect tracking and test management tools such as JIRA, ALM, Azure DevOps, or equivalent tools.

Experience performing regression, integration, system, data migration, and data quality testing.

Understanding of SDLC and structured testing practices.

Ability to collaborate with developers, data engineers, analysts, business stakeholders, and testing teams.

Preferred Experience working in Agile/Scrum environments.

Exposure to continuous integration, continuous delivery, automated test execution, or test reporting practices.

Experience participating in sprint ceremonies, test estimation, defect triage, release planning, and retrospectives.

Security Protocols Essential

Understanding of secure handling of business, customer, transactional, and other sensitive data during testing.

Ability to follow access-control, data privacy, masking, audit, and environment-specific data handling requirements.

Awareness of secure database connectivity and controlled use of test data.

Ability to comply with Synechron’s applicable security, quality, and data protection standards.

Preferred Experience testing data solutions in regulated or controlled environments.

Exposure to data masking, encryption, role-based access, audit logging, and security validation requirements.

Familiarity with security considerations for cloud data platforms and ETL integrations.

Experience Requirements

5–8 years of professional experience in ETL testing, data warehouse testing, database testing, or related data quality assurance roles.

Strong hands‑on experience validating ETL workflows, data migration, data transformation, data loading, and source-to-target processing.

Demonstrated experience writing complex SQL queries for data validation, reconciliation, completeness checks, consistency checks, and defect investigation.

Experience validating large data volumes and transformation logic across data warehouse structures.

Basic practical experience using Python for scripting, automation support, data comparison, and data validation.

Experience using at least one ETL tool, such as Informatica, Talend, SSIS, DataStage, or a similar platform.

Experience with defect tracking, test management, test reporting, and collaboration with development teams.

Experience with Agile/Scrum delivery environments is preferred.

Exposure to cloud data platforms and BI reporting validation is preferred.

Candidates may qualify through equivalent professional experience in data quality testing, database quality assurance, data migration testing, or ETL development roles where they can demonstrate comparable testing outcomes and technical capability.

Day-to-Day Activities

Validate ETL workflows, data transformations, migrations, and loading processes by executing SQL-based source-to-target checks and reconciliation activities.

Prepare and execute test cases, test scenarios, test scripts, regression tests, integration tests, system tests, and data quality validations.

Collaborate with developers, data engineers, analysts, business stakeholders, and testing teams through requirement discussions, defect triage, and delivery meetings.

Use basic Python scripts and approved testing tools to compare data, support repeatable validation, report defects, maintain test evidence, and make testing decisions within approved quality standards.

Qualifications

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field; equivalent relevant professional experience may be considered.

5–8 years of experience in ETL testing, data warehouse testing, database testing, or a closely related data quality role.

Practical training in ETL testing, SQL, data warehousing, database testing, and basic Python scripting is required.

Certifications in software testing, data management, ETL technologies, cloud platforms, or Agile delivery are preferred but not required.

Commitment to continuous professional development through relevant training, tool updates, testing practices, data quality learning, and evolving technology standards.

Professional Competencies

Apply structured analytical and troubleshooting skills to identify data discrepancies, investigate root causes, and validate effective resolutions.

Collaborate with development, data engineering, business, and testing teams to coordinate activities and support shared delivery outcomes.

Communicate test results, risks, defects, dependencies, data issues, and recommendations clearly to technical and non-technical stakeholders.

Adapt to changing requirements, data structures, ETL tools, delivery methods, environments, and testing priorities.

Identify practical opportunities to improve test coverage, reusable validation assets, automation support, data quality, and efficient use of testing resources.

Manage time and priorities across test planning, execution, defect management, documentation, stakeholder coordination, retesting, and release commitments.