BC
Testing Engineer
Accepting applicationsBahwan CyberTek · Greater Chennai Area
Full-Time Mid Pythonaiaterf
Posted
4d ago
Category
Test
Experience
Mid
Country
India
Role description
We are seeking a Testing Engineer to support the Precision Animal Data Lake (PADL) as part of the PADL Engineering Delivery Team within Precision Animal Health.
This role will enhance quality and reliability across our Databricks-based data platform by implementing automated testing for Databricks pipelines, establishing practical data quality validations, and integrating tests into CI/CD.
The Testing Engineer will implement and maintain automated tests (unit, integration, end-to-end, regression, and performance), develop data quality validations aligned to business rules, and integrate tests into GitHub Actions with clear reporting and pass/fail gates.
This position partners closely with data engineers and the Data Analyst to translate requirements into testable acceptance criteria, troubleshoot test failures, support root-cause analysis, and contribute to corrective and preventive actions.
The ideal candidate brings experience in a Testing Engineer, QA, or test automation role with working proficiency in Python (pytest), SQL, and familiarity with CI/CD concepts and Git-based workflows.
Test Automation & Pipeline Testing
• Implement and maintain automated tests for Databricks pipelines (unit, integration, end-to-end, and regression; performance testing as appropriate).
• Develop and maintain repeatable test harnesses and test data strategies to support reliable pipeline testing.
• Design and execute test plans, test cases, and test scripts for data pipelines and ETL/ELT workflows.
• Perform functional, regression, smoke, and sanity testing across data platform components
Data Quality Validation
• Implement data quality validations aligned to business rules (e.g., completeness, uniqueness, referential integrity, thresholds, and reconciliations).
• Support evaluation and adoption of a data quality framework/tooling approach (e.g., Great Expectations or similar).
• Validate data accuracy, consistency, and integrity across Bronze/Silver/Gold data layers.
CI/CD Integration & Test Reporting
• Integrate tests into GitHub Actions with clear reporting and pass/fail gates.
• Maintain test execution logs, defect tracking, and test coverage metrics.
• Ensure automated tests run as part of the deployment pipeline with actionable feedback.
Collaboration & Requirements
• Partner with data engineers and the Data Analyst to translate requirements into testable acceptance criteria and test cases.
• Collaborate with cross-functional stakeholders including ZTD Infrastructure, IT, business, and Information Security teams to evolve testing solutions.
• Work closely with business partners to ensure quality expectations are met in a timely and cost-effective manner.
Troubleshooting & Root-Cause Analysis
• Troubleshoot test failures, support root-cause analysis, and contribute to corrective and preventive actions.
• Identify, document, and track defects through resolution, ensuring clear reproduction steps and severity classification.
• Drive continuous improvement in test coverage, reliability, and execution efficiency.
Documentation & Handoff
• Document test strategies, test plans, test results, and defect summaries.
• Support a structured handoff of production defects/bugs to the PADL DevOps Team.
• Maintain test documentation (validation checklists, test data catalogs) accessible to the broader team.
Required Qualifications:
• Experience in a Testing Engineer, QA, or test automation role (or equivalent hands-on experience).
• Working proficiency in Python and experience with pytest (or an equivalent testing framework).
• Working proficiency in SQL for validation and reconciliation.
• Familiarity with CI/CD concepts and Git-based workflows (GitHub Actions preferred).
• Demonstrated experience working in a software/data development lifecycle (e.g., requirements, acceptance criteria, UAT support).
• Strong ability to translate stakeholder needs into clear, testable requirements and communicate effectively with technical teams.
• Strong SQL skills and experience working with large datasets.
• Familiarity with modern data environments and tooling (e.g., Databricks, ETL/ELT concepts, Azure, ADF, Python).
• Experience with governed data environments and well-defined metric/rule management practices.
Preferred Qualifications:
• Exposure to animal health, dairy, or herd management data domains.
• Experience with data quality frameworks/tools (e.g., Great Expectations, dbt tests, or similar).
• Experience with Spark/Delta optimization (partitioning, file sizing, performance tuning).
• Experience with test management tools (e.g., Jira, TestRail, Zephyr, or similar).
• Experience in healthcare/Life Sciences is preferred but not required.
• Knowledge/experience in DevOps and Agile methodologies
Technical Skills:
• Python (pytest, unittest) for automated test development
• SQL for data validation, reconciliation, and quality checks
• Familiarity with Azure Databricks, Azure Data Factory (ADF), and modern cloud data platforms
• Understanding of ETL/ELT concepts, data pipeline workflows, and lakehouse architecture
• CI/CD pipelines using GitHub Actions — test integration, reporting, and pass/fail gates
• Git-based version control and collaborative development workflows
• Data quality frameworks and tooling (e.g., Great Expectations, dbt tests)
• Test types: unit testing, integration testing, end-to-end testing, regression testing, performance testing
• Test harness development and test data management strategies
• Defect tracking and test management tools (e.g., Jira, TestRail, Zephyr)
• Understanding of data governance, Unity Catalog, and access controls
Show more Show less
We are seeking a Testing Engineer to support the Precision Animal Data Lake (PADL) as part of the PADL Engineering Delivery Team within Precision Animal Health.
This role will enhance quality and reliability across our Databricks-based data platform by implementing automated testing for Databricks pipelines, establishing practical data quality validations, and integrating tests into CI/CD.
The Testing Engineer will implement and maintain automated tests (unit, integration, end-to-end, regression, and performance), develop data quality validations aligned to business rules, and integrate tests into GitHub Actions with clear reporting and pass/fail gates.
This position partners closely with data engineers and the Data Analyst to translate requirements into testable acceptance criteria, troubleshoot test failures, support root-cause analysis, and contribute to corrective and preventive actions.
The ideal candidate brings experience in a Testing Engineer, QA, or test automation role with working proficiency in Python (pytest), SQL, and familiarity with CI/CD concepts and Git-based workflows.
Test Automation & Pipeline Testing
• Implement and maintain automated tests for Databricks pipelines (unit, integration, end-to-end, and regression; performance testing as appropriate).
• Develop and maintain repeatable test harnesses and test data strategies to support reliable pipeline testing.
• Design and execute test plans, test cases, and test scripts for data pipelines and ETL/ELT workflows.
• Perform functional, regression, smoke, and sanity testing across data platform components
Data Quality Validation
• Implement data quality validations aligned to business rules (e.g., completeness, uniqueness, referential integrity, thresholds, and reconciliations).
• Support evaluation and adoption of a data quality framework/tooling approach (e.g., Great Expectations or similar).
• Validate data accuracy, consistency, and integrity across Bronze/Silver/Gold data layers.
CI/CD Integration & Test Reporting
• Integrate tests into GitHub Actions with clear reporting and pass/fail gates.
• Maintain test execution logs, defect tracking, and test coverage metrics.
• Ensure automated tests run as part of the deployment pipeline with actionable feedback.
Collaboration & Requirements
• Partner with data engineers and the Data Analyst to translate requirements into testable acceptance criteria and test cases.
• Collaborate with cross-functional stakeholders including ZTD Infrastructure, IT, business, and Information Security teams to evolve testing solutions.
• Work closely with business partners to ensure quality expectations are met in a timely and cost-effective manner.
Troubleshooting & Root-Cause Analysis
• Troubleshoot test failures, support root-cause analysis, and contribute to corrective and preventive actions.
• Identify, document, and track defects through resolution, ensuring clear reproduction steps and severity classification.
• Drive continuous improvement in test coverage, reliability, and execution efficiency.
Documentation & Handoff
• Document test strategies, test plans, test results, and defect summaries.
• Support a structured handoff of production defects/bugs to the PADL DevOps Team.
• Maintain test documentation (validation checklists, test data catalogs) accessible to the broader team.
Required Qualifications:
• Experience in a Testing Engineer, QA, or test automation role (or equivalent hands-on experience).
• Working proficiency in Python and experience with pytest (or an equivalent testing framework).
• Working proficiency in SQL for validation and reconciliation.
• Familiarity with CI/CD concepts and Git-based workflows (GitHub Actions preferred).
• Demonstrated experience working in a software/data development lifecycle (e.g., requirements, acceptance criteria, UAT support).
• Strong ability to translate stakeholder needs into clear, testable requirements and communicate effectively with technical teams.
• Strong SQL skills and experience working with large datasets.
• Familiarity with modern data environments and tooling (e.g., Databricks, ETL/ELT concepts, Azure, ADF, Python).
• Experience with governed data environments and well-defined metric/rule management practices.
Preferred Qualifications:
• Exposure to animal health, dairy, or herd management data domains.
• Experience with data quality frameworks/tools (e.g., Great Expectations, dbt tests, or similar).
• Experience with Spark/Delta optimization (partitioning, file sizing, performance tuning).
• Experience with test management tools (e.g., Jira, TestRail, Zephyr, or similar).
• Experience in healthcare/Life Sciences is preferred but not required.
• Knowledge/experience in DevOps and Agile methodologies
Technical Skills:
• Python (pytest, unittest) for automated test development
• SQL for data validation, reconciliation, and quality checks
• Familiarity with Azure Databricks, Azure Data Factory (ADF), and modern cloud data platforms
• Understanding of ETL/ELT concepts, data pipeline workflows, and lakehouse architecture
• CI/CD pipelines using GitHub Actions — test integration, reporting, and pass/fail gates
• Git-based version control and collaborative development workflows
• Data quality frameworks and tooling (e.g., Great Expectations, dbt tests)
• Test types: unit testing, integration testing, end-to-end testing, regression testing, performance testing
• Test harness development and test data management strategies
• Defect tracking and test management tools (e.g., Jira, TestRail, Zephyr)
• Understanding of data governance, Unity Catalog, and access controls
Show more Show less