Automation Tester

Job Title: Test Automation Engineer

Experience Required: 2+ Yrs. of very recent experience

Work Location: Gurugram, Haryana (Regular Work from Office)

Work Timings: 04:30 PM 01:30 AM IST (Monday Friday)

Employer Company: Alldomainsoft.com Pvt. Ltd. (alldomainsoft.com)

US Client: Avive Solutions, Inc. (avive.life)

Note: Local candidates preferred. Unsuitable for Java based profiles.

About the Role

As a Test Automation Engineer at Avive, you will play a critical role in ensuring the quality and reliability of our software products. You will build and maintain automated test coverage using Python, Pytest, and BDD frameworks alongside Selenium, focused on validating web application behavior, data accuracy, user permissions, and simulated device communication protocols. Partnering closely with Software Engineering, you will help shape test strategy and expand coverage as new features and functionality are shipped.

What You'll Do including but not limited to:

1. Test Automation Development Design, build, and maintain automated test suites using Python, pytest, and BDD frameworks to validate web application functionality.

• Develop and maintain Selenium-based automation to verify data is displayed accurately across the website.
• Create automation that simulates device communication protocols to validate that data generated by connected devices is correctly received, processed, and reflected on the website.

2. Software Verification

• Expand and maintain automated regression suites that catch defects early and give the team confidence as new features are released.
• Identify gaps in existing test coverage and prioritize new automation based on risk and impact.
• Investigate test failures, determine root cause, and work with Software Engineering to resolve issues.

3. Process & Tooling

• Document, organize, and maintain test cases in Jira using Xray, ensuring traceability between requirements, test coverage, and results.
• Report, track, and prioritize bugs in Jira, working with Software Engineering through resolution.
• Evaluate and integrate new tools, libraries, or frameworks that improve test efficiency, coverage, or maintainability.
• Contribute to CI/CD pipeline integration for automated test execution.
• Continuously refine test strategy and best practices as the product and codebase evolve.

Who You Are

• BS/B.Tech./B.E. in Computer Science, Software Engineering, or a related field (equivalent experience considered).
• 2+ years of experience in software test automation.
• Strong proficiency in Python, with hands-on experience using pytest and BDD frameworks (e.g., pytest-bdd, Behave, or Cucumber)
• Solid experience building and maintaining automated UI tests with Selenium.
• Experience testing web applications, including validating data accuracy, user permissions/access control, and integrations with external or simulated data sources.
• Familiarity with Jira and Xray (or similar tools) for bug tracking and test case management.
• Comfortable working with APIs and simulating device or system communication protocols for test purposes.
• Exposure to CI/CD pipelines and integrating automated tests into a continuous delivery workflow is a plus.
• Strong analytical and debugging skills, with the ability to trace issues from symptom to root cause.
• Organized, independent, and results-oriented, with the ability to manage multiple test efforts simultaneously.
• Excellent communication skills and strong attention to detail, with a collaborative, process-oriented approach to working with Software Engineering.

LinkedIn: www.linkedin.com/in/rkd94

Apply Link: https://jobs.lever.co/AviveSolutions/c20d1002-7998-4e8b-9209-0a4c590d0c7c

Senior Automation Testing Engineer

Location: Bengaluru / Gurugram – Onsite

Experience: 5–11 Years

Employment Type: Full-Time

Key Responsibilities

• Develop and maintain automation test frameworks and scripts.
• Perform both manual and automation testing, including exploratory, functional, regression, and bug verification.
• Develop test cases and contribute to test planning, estimation, and Agile ceremonies.
• Perform non-functional testing for accuracy, reliability, and performance.
• Drive QA process and automation improvements.

Required Skills

• BE/B.Tech/ME/M.Tech in CS/ECE/EE or related field.
• 5–11 years of software testing experience.
• Strong hands-on experience with Python/Java, Selenium, Cucumber, and PyTest.
• Good knowledge of SDLC, testing methodologies, defect lifecycle, and risk assessment.
• Experience with version control and bug-tracking tools.

Good to Have: Linux, Qt/QML, Squish, ISTQB/CSM/PSM, and regulatory/compliance standards.

Job Description

Role: Python Automation

Experience; 3+ years

Location: Bengaluru

Work mode: Hybrid

Interview Mode: Face to face - mandatory

Who are we looking for?

Technical Skills:

Mandatory

• 3 years experience in Python automation and Selenium
• Strong hands-on experience in Python programming and automation.
• Good experience with Selenium WebDriver and web application automation.
• Experience with Pandas, Excel, CSV, JSON, Regex, and file handling.
• Understanding of HTML, CSS, JavaScript, and web application concepts.
• Familiarity with Git/GitHub and Jenkins/CI-CD.
• Good debugging, problem-solving, analytical, and communication skills.

Process Skills:

• Experience with PyAutoGUI or desktop automation.
• Experience working in Linux and Windows environments.
• Knowledge of automation frameworks and software testing practices.

Behavioral Skills:

• Attitude towards learning new technologies and solving complex technical problems.
• Quick learner and team player
• Excellent communication skills

Certification/Qualification:

• Education qualification: B.Tech, BE, or equivalent technical degree from a reputed college linkedin post

Job Description

Role: QA Automation Engineer (Python)

Experience: 5 - 8 Years

Location: Remote (India)

Working Hours: 2:00 PM – 11:00 PM IST

Job Overview

We are seeking a highly skilled and versatile QA Automation Engineer with 5 to 8 years of experience. The ideal candidate possesses a strong blend of manual testing foundations and multi-language automation expertise across desktop, web, and backend services. Hands-on experience with Python (Playwright, PyTest, Pywinauto), Java with Selenium/WinAppDriver, Rest Assured, and the mortgage domain is essential.

Key Responsibilities

• Design and develop automation test scripts using Python, Playwright, Pywinauto, and PyTest.
• Build and maintain automation frameworks for desktop applications using Java (WinAppDriver & Selenium) and Python (Pywinauto).
• Create and execute API automation suites using Rest Assured for RESTful web services.
• Write and execute SQL queries to validate backend data integrity and workflow state transitions.
• Apply mortgage domain expertise across modules such as loan origination, servicing, payments, compliance, and default workflows.
• Manage test cases, defect reporting, and CI/CD automated pipeline execution within Azure DevOps.

Key Requirements

• 5+ years of end-to-end Quality Assurance experience covering both manual and automation testing.
• Multi-Framework & Language Proficiency: Proven hands-on delivery using Python (Pywinauto, PyTest, Playwright) and Java with Selenium/WinAppDriver.
• API & Database Validation: Solid experience with Rest Assured for API testing and complex SQL for relational database verification.
• Domain Experience: Prior working experience in the mortgage or lending domain (origination, servicing, compliance) is mandatory.
• Cross-Platform Testing: Strong background testing both desktop and modern web applications across varied environments.
• DevOps & Tooling: Working knowledge of Azure DevOps CI/CD pipelines, Git version control, and Maven dependency management.

Candidate Profile

• Clear, professional communication skills for seamless collaboration with distributed global teams.
• Strong multitasking abilities to balance framework design, script authoring, and defect triaging.
• Comfortable working the designated evening shift hours (2:00 PM – 11:00 PM IST).

Job Description – QA & Data Validation Engineer

Experience: 5–6 Years

Location: Pan India

Employment Type: Full-Time

Work Mode: Pan India / Remote or Hybrid as applicable

About the Role

We are looking for an experienced QA & Data Validation Engineer with 5–6 years of hands-on experience in data quality assurance, solution analysis, data validation, SQL, Python, PySpark, Azure Data Factory, Azure Synapse Analytics, and Power BI validation.

The ideal candidate will be responsible for validating large-scale data pipelines, performing source-to-target reconciliation, analyzing business rules, investigating data defects, and ensuring the accuracy, completeness, and consistency of data across source, staging, intermediate, and target systems.

The role requires strong analytical and problem-solving skills along with the ability to work closely with development, data engineering, business, and other stakeholders in an Agile delivery environment.

You will also contribute to the design, development, and maintenance of automated validation frameworks and utilities using Python, SQL, PySpark, Azure Data Factory, and Azure Synapse.

---

Key Responsibilities

1. QA & Solution Analysis

- Analyze business and technical requirements to understand data processing and validation needs.

- Participate in requirement analysis sessions and clarify functional and technical requirements with stakeholders.

- Review solution designs, data flows, mapping documents, interface specifications, and business rules.

- Validate that implemented solutions meet defined business and technical requirements.

- Identify gaps, inconsistencies, ambiguities, and potential data quality issues during requirement and solution analysis.

- Translate business requirements into detailed test scenarios, test cases, and validation conditions.

- Perform end-to-end validation of data processing workflows.

- Ensure data is accurately processed from source systems through intermediate layers to final outputs.

- Validate business rules and transformation logic implemented within data pipelines.

2. Test Planning & Execution

- Prepare comprehensive test strategies, test plans, test scenarios, and test cases for data-intensive applications.

- Execute functional, integration, regression, system, and data validation testing.

- Perform positive and negative testing for different data processing scenarios.

- Validate data pipelines across multiple environments, including staging, testing, and production.

- Identify test data requirements and prepare appropriate datasets for validation.

- Execute SQL queries to validate data processing and transformation results.

- Document test results, observations, defects, and validation evidence.

- Track testing progress and communicate status, risks, issues, and dependencies to stakeholders.

3. Data Validation & Reconciliation

- Perform detailed source-to-target data validation and reconciliation.

- Validate source, intermediate, staging, and output datasets.

- Perform record count validation between source and target systems.

- Verify data completeness, consistency, accuracy, and integrity.

- Validate data transformations against defined business rules.

- Perform field-level and record-level comparisons.

- Validate data types, formats, precision, scale, and null handling.

- Verify schema structure, layout, column names, and column sequence.

- Validate mandatory and optional fields.

- Identify missing, duplicate, truncated, or incorrectly transformed records.

- Analyze invalid records, rejected records, and exception datasets.

- Verify exception and reject-handling mechanisms.

- Compare production and staging data to identify discrepancies.

- Perform reconciliation between files, databases, and reporting layers.

- Validate data across different processing stages and identify the root cause of discrepancies.

4. File & Data Processing Validation

- Validate large-scale datasets across multiple file formats.

- Perform validation of:

 - CSV files

 - Delimited files

 - Fixed-width files

 - Excel files

 - Database tables

 - Structured and semi-structured datasets

- Validate file layouts, headers, delimiters, record formats, and column sequences.

- Verify file-level and record-level counts.

- Analyze source, intermediate, and final output files.

- Validate file-to-database and database-to-file reconciliation.

- Identify incomplete, corrupted, malformed, or invalid records.

- Verify data movement and transformation between different storage locations.

- Validate Azure-to-AWS file transfer processes.

- Ensure transferred files are complete and match the expected source datasets.

---

5. Defect Investigation & Root Cause Analysis

- Investigate data discrepancies and application/data pipeline defects.

- Perform detailed root cause analysis for data quality and validation failures.

- Analyze source data, transformation logic, pipeline execution, database records, and output datasets to identify defects.

- Collaborate with developers and data engineers to resolve identified issues.

- Reproduce defects and provide detailed technical evidence.

- Perform defect impact analysis.

- Conduct retesting and regression testing after defect resolution.

- Monitor recurring data quality issues and recommend preventive solutions.

- Maintain detailed defect documentation and validation results.

---

6. Python Development & Automation

- Develop Python scripts and utilities for data validation and reconciliation.

- Design, develop, and maintain reusable data validation frameworks.

- Automate repetitive data comparison and validation activities.

- Build automated utilities for:

 - Record count validation

 - Data completeness checks

 - Schema validation

 - Column sequence validation

 - Source-to-target comparison

 - Duplicate detection

 - Exception identification

 - Data quality checks

 - Automated reporting

- Develop Python-based validation and reporting utilities.

- Optimize Python scripts for processing large datasets.

- Maintain and enhance existing automation frameworks.

- Implement reusable validation components to improve testing efficiency and coverage.

---

7. SQL Development & Data Analysis

- Write complex SQL queries for data analysis and validation.

- Perform data extraction and comparison using SQL Server / SSMS.

- Validate source and target database records.

- Perform joins, aggregations, subqueries, CTEs, and analytical queries as required.

- Develop SQL queries to identify data mismatches, duplicates, missing records, and transformation issues.

- Validate database tables, schemas, columns, constraints, and relationships.

- Perform record count and reconciliation checks using SQL.

- Analyze SQL Server metrics databases.

- Validate data processing results against expected business rules.

- Troubleshoot data discrepancies using SQL queries.

---

8. PySpark & Large-Scale Data Processing

- Develop and execute PySpark notebooks for large-scale dataset processing and validation.

- Analyze large volumes of structured and semi-structured data.

- Perform data transformation and validation using PySpark.

- Compare large source and target datasets efficiently.

- Implement data quality and reconciliation checks using PySpark.

- Analyze exception, reject, and invalid datasets.

- Optimize data validation processes for large datasets.

- Work with Azure Synapse notebooks and data processing environments.

---

9. Azure Data Factory & Pipeline Testing

- Design and execute validation scenarios for Azure Data Factory (ADF) pipelines.

- Validate pipeline execution, data movement, transformations, and dependencies.

- Monitor pipeline runs and investigate failures.

- Validate source-to-target data movement through ADF.

- Develop and maintain test pipelines using Azure Data Factory.

- Verify pipeline parameters, triggers, activities, and execution results.

- Validate file ingestion and processing workflows.

- Perform end-to-end testing of data pipelines.

- Investigate pipeline-related data discrepancies and failures.

---

10. Azure Synapse Analytics

- Work with Azure Synapse Analytics for data validation and analysis.

- Develop and execute Synapse notebooks using PySpark.

- Validate datasets processed through Synapse pipelines and notebooks.

- Perform data quality and reconciliation checks within Synapse environments.

- Analyze large-scale datasets and processing results.

- Validate data movement between Azure storage, Synapse, databases, and reporting systems.

---

11. Azure Storage & Cosmos DB

- Validate data stored in Azure Storage Accounts and Containers.

- Verify file ingestion, processing, and output data.

- Perform file-level and content-level validation within Azure storage.

- Validate data processing workflows involving Azure Storage.

- Perform data validation in Azure Cosmos DB.

- Verify records, fields, formats, and data completeness within Cosmos DB.

- Investigate discrepancies between source files, Azure storage, databases, and Cosmos DB.

---

12. AWS S3 & Azure-to-AWS Validation

- Validate files stored in AWS S3.

- Perform source-to-target validation for files transferred between Azure and AWS.

- Verify file counts, file names, sizes, formats, and record counts.

- Compare source files with transferred S3 files.

- Validate data integrity after cloud-to-cloud file transfers.

- Investigate missing, incomplete, duplicate, or corrupted files.

- Support end-to-end validation of Azure-to-AWS data movement processes.

---

13. Metrics, Reporting & Power BI Validation

- Extract and validate source system metrics.

- Validate metrics stored in SQL Server databases.

- Perform reconciliation between source metrics, database metrics, and reporting outputs.

- Validate Power BI dashboards and reports against underlying source data.

- Verify report calculations, KPIs, measures, filters, and aggregations.

- Perform file-to-database-to-Power BI reconciliation.

- Validate data displayed in Power BI against SQL Server and source datasets.

- Identify discrepancies between backend data and dashboard results.

- Support reporting and analytics teams with data validation and troubleshooting.

---

14. Production Support & Job Monitoring

- Monitor scheduled data processing jobs and pipelines.

- Perform production validation and health checks.

- Analyze production failures and data discrepancies.

- Support incident investigation and resolution.

- Compare production and staging environments to identify differences.

- Validate production data after deployments and pipeline executions.

- Monitor ECG jobs and provide support for job execution and data processing issues.

- Perform post-production validation and reconciliation.

- Communicate critical production issues and risks to relevant stakeholders.

---

15. Agile Delivery & Stakeholder Collaboration

- Work effectively within an Agile/Scrum delivery environment.

- Participate in sprint planning, daily stand-ups, backlog refinement, sprint reviews, and retrospectives.

- Collaborate with Business Analysts, Developers, Data Engineers, DevOps teams, Product Owners, and other stakeholders.

- Provide timely updates on testing progress and issues.

- Participate in requirement clarification and solution discussions.

- Support release planning and production deployment activities.

- Track work items and defects using Rally.

- Ensure testing activities are aligned with sprint and release timelines.

---

Required Technical Skills

Mandatory Skills

- 5–6 years of experience in QA / Data Validation / Data Testing / Data Quality Engineering.

- Strong experience in SQL and data analysis.

- Hands-on experience with Python development and automation.

- Experience with PySpark and large-scale data processing.

- Strong experience with Azure Data Factory (ADF).

- Experience with Azure Synapse Analytics / Synapse Pipelines / Notebooks.

- Strong understanding of source-to-target data validation and reconciliation.

- Experience in data completeness, record count, schema, layout, and column validation.

- Experience in defect investigation and root cause analysis.

- Experience validating large datasets and multiple file formats.

- Experience with SQL Server / SSMS.

- Experience with Power BI dashboard/report validation.

- Strong understanding of data pipelines and ETL/ELT processes.

Cloud & Data Platform Experience

- Azure Data Factory

- Azure Synapse Analytics

- Azure Synapse Pipelines

- Azure Synapse Notebooks

- Azure Storage Accounts

- Azure Storage Containers

- Azure Cosmos DB

- Azure Privileged Identity Management (PIM)

- AWS S3

- Azure-to-AWS file transfer validation

---

Preferred Skills

- Experience developing automated data validation frameworks.

- Experience building automated reporting and reconciliation utilities.

- Knowledge of ETL/ELT testing methodologies.

- Experience working with very large datasets.

- Experience in production data validation and support.

- Knowledge of cloud-based data platforms.

- Experience with Power BI data reconciliation.

- Experience working in Agile environments.

- Experience with Rally or similar Agile project management tools.

- Familiarity with Microsoft Copilot and AI-assisted productivity/automation tools.

---

Key Responsibilities at a Glance

The successful candidate will be responsible for:

- Requirement analysis and clarification

- Business rule validation

- Test planning and execution

- Data quality and data validation

- Source-to-target reconciliation

- Record count and completeness validation

- Schema and layout validation

- Column sequence validation

- Exception and reject data analysis

- Production vs. staging comparison

- SQL-based data analysis

- Python automation

- PySpark development

- Azure Data Factory pipeline testing

- Azure Synapse validation

- Azure Storage validation

- Cosmos DB validation

- AWS S3 validation

- Azure-to-AWS file transfer validation

- Power BI dashboard validation

- SQL Server metrics validation

- Automated reporting

- Defect investigation and root cause analysis

- Production job monitoring and support

- Agile delivery and stakeholder collaboration

---

Candidate Profile

We are looking for a detail-oriented, analytical, and technically strong QA/Data Validation professional who can work independently on complex data validation assignments.

The candidate should be comfortable working with large datasets, writing SQL queries, developing Python automation, analyzing PySpark datasets, validating cloud-based data pipelines, and troubleshooting data discrepancies across multiple systems.

Strong communication and stakeholder management skills are essential, as the role requires regular collaboration with technical and business teams.

---

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field is preferred.

Experience

5–6 years of relevant professional experience in QA, Data Testing, Data Validation, ETL Testing, Data Quality, Data Engineering QA, or a similar role.

Location

Pan India

Employment Type

Full-Time

Keywords

QA Engineer, Data QA, Data Validation, Data Testing, ETL Testing, Data Quality, SQL, Python, PySpark, Azure Data Factory, ADF, Azure Synapse, Synapse Analytics, Synapse Pipelines, Azure Storage, Cosmos DB, AWS S3, Power BI, SQL Server, SSMS, Data Reconciliation, Source-to-Target Validation, Data Pipeline Testing, ETL QA, Automation Testing, Data Analytics, Root Cause Analysis, Agile, Rally, Cloud Data Testing, Data Engineering QA.

SDET – Software Development Engineer in Test

Experience: 2–5 Years

Location: Bangalore / Gurugram

Employment Type: Full-Time

Mandatory Skills

• 2–5 years of relevant experience in SDET / QA Automation / Software Testing.
• Strong hands-on experience in:
• Functional Testing
• API Testing
• Performance Testing
• Good programming/coding skills with the ability to read, write, troubleshoot, and debug code.
• Experience with automation testing frameworks/tools such as Selenium, Playwright, Cypress, Appium, etc.
• Hands-on API testing experience using tools such as Postman, REST Assured, RestSharp, or similar.
• Practical experience with performance testing tools such as JMeter, LoadRunner, k6, Gatling, or equivalent.
• Good understanding of SDLC, STLC, defect lifecycle, and testing methodologies.
• Strong analytical and problem-solving skills.

Good to Have

• Experience with Java, Python, JavaScript/TypeScript, C#, or other programming languages.
• Experience with .NET / C#.
• SQL/database testing experience.
• CI/CD tools such as Jenkins, GitHub Actions, Azure DevOps, GitLab CI, etc.
• Experience with Docker/cloud environments.
• BDD frameworks such as Cucumber or SpecFlow.
• Experience working with Agile/Scrum teams.

If Interested, share CV : snigdhaattheratebeanhr.com

Job Title – Staff QA Automation Engineer

Location - India, Remote

EGNYTE YOUR CAREER. SPARK YOUR PASSION.

Egnyte is a place where we spark opportunities for amazing people. We believe that every role has meaning, and every Egnyter should be respected. With 22,000+ customers worldwide and growing, you can make an impact by protecting their valuable data. When joining Egnyte, you’re not just landing a new career, you become part of a team of Egnyters who doers, thinkers, and collaborators are who embrace and live by our values:

• Invested Relationships
• Fiscal Prudence
• Candid Conversations

ABOUT EGNYTE

Egnyte is the secure multi-cloud platform for content security and governance that enables organizations to better protect and collaborate on their most valuable content. Established in 2008, Egnyte has democratized cloud content security for more than 22,000 organizations, helping customers improve data security, maintain compliance, prevent and detect ransomware threats, and boost employee productivity on any app, any cloud, anywhere. For more information, visit www.egnyte.com.

Egnyte is looking for an experienced Staff QA Automation Engineer to join our team and work on some exciting projects. You should possess excellent communication skills in addition to the desired technical experience.

WHAT YOU’LL DO:

What You’ll Do (but is not limited to):

• Create automated processes to build Egnyte software packages which will be deployed in production environments
• Develop automatic tools to provision build/test environments on cloud infrastructure for hosting internal development and QA activities
• Prepare deployment solutions for QA, staging and production environments
• Create and maintain tools responsible for delivering on-premise services to customer (for example, on-premises server restart and software update)
• Contribute to the development processes, including enhancements to build procedures, test frameworks, verification tools and packaging
• Provide tools and automation workflows to increase software developer productivity
• Assist in defining the process models and tool sets to enable adoption of DevOps methodologies.

Your Qualifications:

• Experience with the Linux operating system, including configuration of subsystems such as storage, networking and file systems
• Strong knowledge of CI/CD tools such Jenkins, git, puppet, ansible, terraform and hands-on experience in implementing automated branching, build, test-automation and deployment pipelines
• Demonstrated abilities of writing and troubleshooting system level scripts in python and bash
• Familiarity with Linux packaging tools such as apt and automated package update mechanisms
• Familiarity with Windows OS internals and experience with QA automation on windows..
• Ability to work with multi-cultural, globally distributed teams to a common unifying product vision and closely coordinate with cross-functional teams in different time-zones.
• Passion to deliver enterprise-grade products to customers and to continuously work with engineering team to refine the product in the field.
• Experience on using AI tools to develop skills, hooks and scheduler

Education and experience:

• Bachelor’s degree in computer science, Computer Engineering or equivalent.
• Minimum 8 years industry experience as a software developer or quality engineer with enterprise software testing.

BENEFITS

• Competitive salaries
• Medical insurance and healthcare benefits for you and your family
• Fully paid premiums for life insurance
• Flexible hours and PTO
• Mental wellness platform subscription
• Gym reimbursement
• Childcare reimbursement
• Group term life insurance

COMMITMENT TO DIVERSITY, EQUITY, AND INCLUSION:

At Egnyte, we celebrate our differences and thrive on our diversity for our employees, our products, our customers, our investors, and our communities. Egnyters are encouraged to bring their whole selves to work and to appreciate the many differences that collectively make Egnyte a higher-performing company and a great place to be.

Any employees with questions or concerns about equal employment opportunities in the workplace are encouraged to bring these issues to the attention of hrategnyte.com. Egnyte will not allow any form of retaliation against employees who raise issues of equal employment opportunity. If employees feel they have been subjected to any such retaliation, they should contact hrategnyte.com. To ensure the workplace is free of artificial barriers, violation of this policy including any improper retaliatory conduct will lead to discipline, up to and including discharge. All employees must cooperate with all investigations conducted pursuant to this policy.

What you'll own

The quality charter. Define and evolve the testing strategy — web application, dashboards, APIs, webhooks, and customer integrations. Establish release criteria, coverage expectations, and quality gates that engineers actually respect because they're fast and they catch real bugs. Automation at scale. Build and maintain end-to-end and API automation suites that run on every PR and give a trustworthy signal. Own the flake rate. Design for parallel execution, deterministic test data, and fast feedback — a suite nobody trusts is worse than no suite. Performance and reliability. Design and run load, stress, and soak tests against APIs and the platform. Profile results, isolate bottlenecks with the engineers who own the service, and set up the monitoring that tells us about degradation before a customer does. Leverage through tooling, including AI. Use whatever gets coverage up and cycle time down: LLM-assisted test case generation from specs, AI-assisted authoring and maintenance of automation, synthetic test data generation, log and failure triage. We expect you to be opinionated about where these tools genuinely help and where they produce impressive-looking noise. Raising the bar. Partner with product and engineering from spec through release so quality risk is surfaced during design, not after code freeze. Mentor the QA team and build the practices — bug triage discipline, root cause analysis, prevention over detection — that outlast any single release.

What we're looking for

Must have

3–6 years in QA roles, with meaningful ownership of automation frameworks rather than only executing existing suites.

Strong test automation skills with a modern framework — Playwright, Cypress, or Selenium — and solid coding ability in Python, JavaScript/TypeScript, or Java. You should be comfortable reading application code, not just testing around it.

API testing experience: REST, auth, webhooks and asynchronous event flows, contract testing, and tooling such as Postman, REST Assured, or Pact.

Hands-on CI/CD integration — GitHub Actions, GitLab CI, Jenkins, or equivalent — including making suites fast and reliable enough to gate merges.

Working knowledge of SQL for validating data correctness, and comfort with logs, traces, and observability tooling for debugging.

Rigorous, systematic thinking about edge cases and failure modes, and the communication skills to make quality risk legible to product and leadership.

Nice to have

Experience testing AI, ML, or LLM-based products, and comfort with the reality that outputs are probabilistic rather than deterministic. Familiarity with Docker, Kubernetes, or cloud infrastructure for standing up test environments.

Performance and load testing with k6, JMeter, Gatling, or Locust, plus the analytical ability to turn results into a specific, actionable bottleneck. Exposure to enterprise SaaS with real integration surface area, or to security and compliance testing expectations of enterprise buyers. - Experience as the first or most senior quality voice on a team.

What we offer

Competitive compensation with equity. Direct ownership of a charter that materially affects how enterprise customers experience our product.

Proximity to frontier AI systems in production, and the freedom to use modern tooling to do your job well.

A fast-moving team where the distance between an idea and a shipped change is short.

Who are we?

Trendlyne is a funded, profitable products startup in the financial markets space. We have cutting-edge analytics products built for Indian and US customers, for stock markets and mutual funds.

Our founders are IIT + IIM graduates, with strong tech and marketing experience. We have top finance and management experts on the Board of Directors.

What do we do?

We build powerful analytics in the US and Indian stock market space that are best in class. Organic growth in B2B and B2C products have already made the company profitable. We deliver 1 billion+ APIs every month to B2B customers, and have a B2C website and app.

Tech Stack :

• Postman
• Playwright
• Jenkins

Job Responsibilities :

• Design, develop, and maintain scalable UI and API automation frameworks from scratch.
• Build and execute automated test suites for frontend, backend, and API applications using tech stacks like Playwright, Selenium, and Postman.
• Develop automation for web applications, APIs, and distributed microservices.
• Perform white-box and black-box testing to ensure application quality.
• Integrate automation suites into CI/CD pipelines using tools like Newman and Bruno CLI.
• Identify, track, and resolve defects while improving test stability, execution speed, and overall automation efficiency.
• Collaborate with developers, DBAs, and product managers to ensure quality throughout the development lifecycle.
• Drive continuous improvements in automation frameworks, testing methodologies, and engineering processes.

Required Skills & Qualifications :

• 1-3 years of experience as an SDET, Automation Engineer, or Full-Stack QA.
• Experience with UI automation using Playwright and Selenium.
• Strong experience in API testing and automation using Postman.
• Proficient in JavaScript for building automation scripts, API test assertions, and test utilities.
• Experience with white-box and black-box testing, and automation design patterns such as Page Object Model (POM).
• Familiarity with BDD frameworks (e.g., Cucumber) and modern testing practices.
• Experience with Git and integrating automation suites into CI/CD pipelines using Jenkins, GitHub Actions, or GitLab CI.
• Working knowledge of SQL for database validation and backend testing.

Job Summary

We are looking for an experienced ETL Tester / Data QA Engineer with strong SQL skills to validate data pipelines, ETL processes, data transformations, and data quality across source and target systems. The candidate should have hands-on experience in writing complex SQL queries, performing data validation, and identifying data discrepancies.

Key Responsibilities

• Perform ETL testing for data extraction, transformation, and loading processes.
• Validate data between source and target systems.
• Write and execute complex SQL queries for data validation and reconciliation.
• Verify data transformations, mappings, joins, aggregations, and business rules.
• Perform data completeness, accuracy, consistency, integrity, and duplicate checks.
• Validate incremental and full data loads.
• Test ETL workflows, batch jobs, and data pipelines.
• Identify, document, and track defects using tools such as JIRA.
• Analyze production data issues and support root-cause analysis.
• Prepare test scenarios, test cases, test data, and execution reports.
• Work closely with developers, data engineers, business analysts, and other QA teams.
• Participate in regression, integration, system, and end-to-end testing.

Required Skills

• Strong hands-on experience in ETL/Data Warehouse Testing.
• Advanced SQL skills, including:
• Joins
• Subqueries
• CTEs
• Window functions
• Aggregations
• Stored procedures
• Data reconciliation
• Knowledge of Data Warehousing concepts such as fact and dimension tables, star/snowflake schemas, and slowly changing dimensions (SCD).
• Experience with ETL tools such as Informatica, Talend, SSIS, DataStage, or similar.
• Experience with relational databases such as Oracle, SQL Server, PostgreSQL, or MySQL.
• Good understanding of SDLC/STLC and defect life cycle.
• Experience with Agile/Scrum methodologies.

Good to Have

• Experience with cloud data platforms such as Snowflake, AWS, Azure, or GCP.
• Knowledge of tools such as Databricks, Azure Data Factory, AWS Glue, or dbt.
• Experience with API testing or data pipeline automation.
• Basic knowledge of Python for test/data validation automation.
• Experience testing large-volume datasets and complex data migrations.

Qualifications

• Bachelor's degree in Computer Science, IT, Engineering, or a related field.
• Strong analytical and problem-solving skills.
• Good communication and documentation skills.