Deloitte Hiring 2026: BTA – Quality Engineer in Hyderabad

Deloitte is hiring for the position of BTA – Quality Engineer in Hyderabad, Telangana, India. This is an entry-level opportunity within the Analytics Horizontal team, focused on quality engineering for enterprise analytics solutions. The role involves testing and validating reports, dashboards, ETL and data pipelines, APIs, and AI-enabled applications to ensure that analytics solutions are reliable, accurate, usable, secure, and performant.

The position is particularly relevant for candidates with a Bachelor’s Degree or equivalent background in Computer Science or a related field who are interested in software testing, data validation, analytics, SQL, API testing, test automation, and emerging AI and GenAI testing practices.

The Deloitte Quality Engineer role provides exposure to multiple areas of modern enterprise technology. Candidates will work with experienced quality engineers and collaborate with developers, analysts, product owners, and business stakeholders. The source describes this as an entry-level position where candidates will receive training on applications, analytics platforms, testing practices, and automation tools while developing a foundation in quality engineering for enterprise analytics.

About Deloitte

Deloitte is a global professional services organization with operations across multiple business and technology domains. Its technology-focused teams work on enterprise applications, analytics, data, cloud, cybersecurity, engineering, and digital transformation initiatives.

This particular opportunity is focused on quality engineering within an analytics environment. Rather than limiting testing activities to traditional web application testing, the role covers several types of enterprise analytics components, including reports, dashboards, APIs, data pipelines, ETL and ELT workflows, and AI-enabled applications.

For candidates starting a career in software testing, the position provides exposure to both application-level and data-level quality validation. This can help candidates understand how requirements are converted into test scenarios, how data is validated between different systems, how defects are documented, and how testing contributes to successful software releases.

Deloitte BTA – Quality Engineer Job Overview

The position is BTA – Quality Engineer and is based in Hyderabad, Telangana, India. The source identifies the opportunity as an entry-level Quality Engineer position within the Analytics Horizontal team.

The role involves supporting the quality and reliability of analytics solutions. Candidates will be expected to understand requirements and acceptance criteria, create structured testing scenarios, execute different forms of testing, validate data, identify defects, support regression testing, and contribute to release-readiness activities.

The role also provides exposure to automation. Candidates may create or maintain reusable scripts for API, user-interface, data-validation, and regression testing under guidance. The position therefore combines manual testing fundamentals with data validation, API testing, automation exposure, analytics testing, and emerging AI application testing.

The location is Hyderabad, and the specified shift timing is 11:00 AM to 8:00 PM.

Understand the Job Role

As a BTA – Quality Engineer, your primary responsibility will be to help ensure that analytics applications and data-driven solutions work correctly and deliver accurate results. Quality engineering in this environment goes beyond simply checking whether an application opens or a button works. You may need to verify data accuracy, calculations, transformations, API responses, dashboard behavior, access controls, integrations, and end-to-end business workflows.

You will work with quality engineering leads, developers, analysts, product owners, and business stakeholders to understand what a solution is expected to do. This means reading requirements, user stories, acceptance criteria, and business rules and converting that information into practical test scenarios.

A major part of the role involves creating and maintaining test scenarios, detailed test cases, test data, requirement traceability information, and testing evidence. Candidates need to understand what should happen under normal conditions as well as what should happen when invalid, unexpected, boundary, or failure conditions occur.

Testing activities can include functional testing, integration testing, system testing, regression testing, retesting, exploratory testing, user-interface testing, API testing, and end-to-end testing. These activities may be performed across reports, dashboards, data pipelines, and AI-enabled applications.

The role also has a significant data-quality component. You may use SQL and source-to-target comparisons to verify whether information has been transferred and transformed correctly between systems. This can involve checking completeness, accuracy, consistency, transformations, reconciliations, refreshes, and exception handling.

Another important area is ETL and ELT testing. Candidates may need to test workflows, file integrations, API integrations, scheduled jobs, and cloud-based data processes. Testing can involve positive scenarios, negative scenarios, boundary conditions, and failure scenarios to ensure that systems behave correctly under different circumstances.

The position also introduces AI-enabled application testing. The source specifically mentions evaluating functional correctness, response relevance, groundedness, guardrails, permissions, error handling, and consistent behavior using approved test data and expected outcomes.

Match Your Skills

Candidates applying for this position should have a foundational understanding of software testing concepts, the software development life cycle, and the defect life cycle. You should understand why software testing is performed and how defects are identified, documented, tracked, retested, and closed.

Basic SQL knowledge is particularly relevant to this position because data validation is an important part of the job. Candidates should be comfortable with concepts such as queries, joins, filters, aggregations, comparisons, and reconciliation checks. SQL can be used to compare source and target data and investigate potential data-quality issues.

Knowledge of data-quality concepts is also useful. The source specifically mentions completeness, accuracy, consistency, uniqueness, validity, and timeliness. Understanding these concepts can help candidates identify whether data is suitable for use in reports, dashboards, analytics platforms, and downstream business processes.

Candidates should also have some familiarity with testing web applications, reports, dashboards, APIs, or data pipelines. This exposure can come through academic coursework, projects, internships, or practical experience.

Basic scripting or programming knowledge is another useful area. The source mentions Python, C#, JavaScript, or a similar programming language. Candidates do not necessarily need to present themselves as advanced software developers, but an understanding of programming and scripting can be valuable for automation and technical testing activities.

The role also mentions exposure to automation tools and frameworks such as Playwright and Selenium, along with API testing tools such as Postman. Candidates who have practiced these tools through projects or learning activities can understand how automated testing fits into a modern quality engineering workflow.

Knowledge of Microsoft Excel is also relevant because Excel may be used for test-data preparation, analysis, reconciliation, and quality-status reporting.

Check Your Eligibility

According to the provided job description, candidates should have a Bachelor’s Degree or equivalent education in Computer Science or a related field.

The source does not specify a particular graduation year, minimum percentage, backlog requirement, age limit, or specific number of years of experience. Therefore, candidates should not assume additional eligibility conditions unless Deloitte provides them through the official application process.

This is described as an entry-level Quality Engineer opportunity. Candidates with relevant exposure through academic projects, internships, coursework, certifications, or practical testing experience may find the listed skills particularly relevant.

The position requires strong analytical thinking, attention to detail, problem-solving ability, and willingness to investigate application and data issues. Communication skills are also important because the role involves documenting defects and explaining findings to both technical and nontechnical stakeholders.

Be Ready With Your Documents

Before applying, candidates should keep their updated resume and educational information ready. Since the position is related to software testing, analytics, data validation, and quality engineering, your resume should clearly present relevant technical skills and projects rather than only listing your degree.

Candidates with academic or personal projects involving SQL, databases, APIs, web applications, dashboards, Python, JavaScript, Selenium, Playwright, Postman, Power BI, or data validation should describe those projects clearly.

If you have completed a software-testing course or certification, the details can also be included. The source specifically mentions relevant software-testing coursework or certification such as ISTQB Foundation Level as an area of interest.

It is also useful to be prepared to explain any testing project in detail. Candidates should understand what they tested, how they created test cases, what data they used, how defects were identified, and how they verified that an issue was resolved.

Deloitte Quality Engineer Responsibilities

One of the central responsibilities is understanding requirements and acceptance criteria. Quality engineers need to know what the business expects from a solution before determining how it should be tested.

Candidates will prepare test scenarios and detailed test cases and maintain supporting test data and evidence. Requirement traceability is also part of the role, helping teams establish a connection between requirements and corresponding testing activities.

The position involves executing different types of testing across analytics solutions. Functional testing checks whether features operate according to requirements, while integration testing examines interactions between systems and components.

Regression testing is important when existing functionality could be affected by new changes. Retesting is used to verify that previously identified defects have been resolved. Exploratory testing can help uncover issues that may not be identified through predefined test cases.

For reports and dashboards, testing may include checking data accuracy, calculations, filters, drill-down behavior, visual behavior, usability, access controls, exports, and performance.

Data validation is another major responsibility. SQL and source-to-target comparisons can be used to verify whether information is complete, accurate, consistent, correctly transformed, reconciled, refreshed, and properly handled when exceptions occur.

Candidates may also test ETL and ELT workflows, file integrations, API integrations, scheduled jobs, and cloud-based data processes.

SQL and Data Validation in This Role

SQL is particularly important because analytics systems depend heavily on accurate data. A dashboard can look visually correct while still presenting incorrect information if the underlying data has been transformed incorrectly.

A Quality Engineer may therefore need to compare data between a source system and a target analytics platform. This can involve checking record counts, comparing values, validating transformations, examining joins, and identifying discrepancies.

For example, if information moves from a source database into an analytics warehouse, the tester may need to confirm that expected records arrive in the destination system and that the transformation rules are applied correctly.

The source specifically highlights joins, filters, aggregations, and reconciliation checks. Candidates preparing for this position should therefore be comfortable with these SQL fundamentals.

Testing Reports and Dashboards

Analytics solutions often depend on reports and dashboards that business users use for decision-making. Testing these solutions requires more than checking whether a dashboard loads successfully.

The Quality Engineer may need to verify whether the numbers shown in reports match the underlying data. Filters should behave according to requirements, drill-downs should lead to the correct information, calculations should be accurate, and exports should contain the expected results.

Access control is another consideration. Different users may have different permissions, so testers need to verify that users can access only the information they are authorized to see.

Usability and visual behavior are also mentioned in the source. This means the testing process can include checking whether dashboards behave as expected from a user perspective.

ETL, APIs and Data Pipeline Testing

Modern analytics environments frequently involve data moving through multiple systems. ETL and ELT processes extract, transform, and load data into destinations where it can be analyzed.

In this position, candidates may test whether those workflows operate correctly. This can involve testing successful processing, incorrect inputs, missing data, integration failures, scheduled jobs, and exception scenarios.

API testing is also included in the role. Candidates with exposure to tools such as Postman can understand how API requests and responses can be tested independently of the user interface.

The role therefore provides exposure to multiple layers of an analytics ecosystem rather than focusing exclusively on front-end application testing.

AI and GenAI Testing Exposure

An important feature of this position is its exposure to AI-enabled applications. The source specifically mentions testing functional correctness, response relevance, groundedness, guardrails, permissions, error handling, and consistent behavior.

AI and GenAI applications can produce outputs that need to be evaluated against approved expectations and test data. A Quality Engineer working in this area may therefore need to understand how to evaluate whether an AI-enabled feature behaves consistently and whether it follows defined restrictions.

The source also mentions retrieval-augmented generation, response evaluation, guardrails, and responsible use of test data. Candidates interested in AI testing can therefore view this role as an opportunity to develop knowledge in an emerging area of quality engineering.

Automation Testing Exposure

The position includes support for test automation. Candidates may create or maintain reusable scripts for API testing, user-interface testing, data validation, and regression testing under guidance.

The source mentions Playwright and Selenium as examples of automation frameworks and Postman for API testing. Candidates who have practical exposure to these technologies can understand how repetitive testing activities can be automated.

Automation does not replace the need for testing fundamentals. Candidates should first understand requirements, expected results, test scenarios, data validation, and defect identification before attempting to automate a workflow.

Tools and Technology Areas

The job description references a broad range of technologies and tools. These include SQL, Microsoft Excel, Azure DevOps, Jira, Python, C#, JavaScript, Playwright, Selenium, Postman, QlikView, Qlik Sense, SSRS, Bold Reports, and Power BI.

The source also mentions ETL and ELT concepts, relational databases, REST APIs, data warehouses, and cloud services including AWS S3, Glue, Redshift, Lambda, and Databricks.

Candidates should not assume that every technology listed is a mandatory requirement. The source presents many of these as familiarity or exposure areas. Candidates should therefore distinguish between foundational testing knowledge and optional or additional technical exposure.

Agile and Software Development Lifecycle

The Quality Engineer will work within an Agile environment and participate in Agile ceremonies, defect triage, test-status reporting, release-readiness activities, and post-release validation.

Understanding the software development lifecycle can help candidates understand where testing fits into the overall development process. Testing is not limited to the final stage of development; quality activities can begin when requirements are discussed and continue through release and post-release validation.

Candidates should also understand the defect lifecycle, including identifying an issue, documenting the problem, providing reproduction information and evidence, tracking the defect, retesting the fix, and confirming the outcome.

The source also mentions version control, CI/CD, release testing, and production validation as relevant areas of understanding.

Defect Management and Quality Reporting

When a defect is identified, the Quality Engineer needs to provide enough information for the development team to reproduce and understand the issue.

The source specifically mentions clear reproduction steps, supporting evidence, expected results, actual results, and business impact. This means defect reporting should be structured and understandable rather than simply stating that something is not working.

Candidates should also be comfortable discussing testing progress and quality status with team members. Maintaining test suites, test data, quality metrics, and supporting documentation is part of the role.

Location and Shift Timing

The Deloitte BTA – Quality Engineer position is based in Hyderabad, Telangana, India.

The specified shift timing is 11:00 AM to 8:00 PM. Candidates considering the opportunity should verify the timing and any additional work-location requirements during the application or recruitment process because the provided source does not provide further details about weekly schedules, work-from-home arrangements, or office-specific policies.

Career Opportunity for Quality Engineering Freshers

This role can expose an entry-level candidate to several areas of software quality engineering. Instead of focusing only on traditional functional testing, the job description combines application testing, data validation, SQL, APIs, dashboards, data pipelines, automation, cloud technologies, and AI-enabled applications.

Candidates can use such an environment to build an understanding of how enterprise analytics solutions are developed and validated.

The combination of testing and data skills is particularly relevant because analytics applications depend on the quality of the underlying data. A tester who understands both application behavior and data validation can participate in a wider range of quality activities.

The role also emphasizes collaboration with developers, analysts, product owners, and business stakeholders, which can help candidates develop communication and requirement-analysis skills alongside technical testing knowledge.

How to Prepare for the Deloitte Quality Engineer Role

Candidates preparing for this opportunity should first revise software-testing fundamentals. Important concepts include functional testing, integration testing, system testing, regression testing, retesting, exploratory testing, positive testing, negative testing, boundary testing, and end-to-end testing.

SQL should receive significant attention because the job description specifically highlights data validation. Candidates should practice SELECT queries, WHERE conditions, JOIN operations, GROUP BY, aggregate functions, filtering, duplicate detection, record comparisons, and basic reconciliation scenarios.

Candidates should also understand how APIs work and practice basic API testing using a tool such as Postman. Understanding request methods, response codes, headers, request bodies, response bodies, and basic validation can provide useful preparation.

For automation, candidates can become familiar with Selenium or Playwright and understand how automated test scripts interact with web applications. Basic programming knowledge in Python, JavaScript, C#, or another suitable language can support this preparation.

Candidates interested in analytics testing should also practice working with Excel and become familiar with dashboards and visualization concepts. Exposure to Power BI or another reporting platform can help candidates understand how analytics outputs are presented to business users.

For AI testing, candidates should understand basic concepts around prompt-based applications, response evaluation, groundedness, guardrails, retrieval-augmented generation, and responsible test-data usage.

Interview Preparation for Quality Engineering

The source does not provide a specific interview-round structure, so candidates should not assume a particular number or sequence of interviews.

However, based on the skills and responsibilities explicitly mentioned in the job description, candidates should be prepared to discuss software-testing fundamentals, SQL, data validation, API testing, defect management, Agile concepts, and basic automation.

Candidates should also be able to explain projects or practical exercises mentioned on their resumes. If you list SQL, Selenium, Postman, Python, Power BI, or another technology, be prepared to explain how you used it.

For project-based questions, it can be useful to explain the objective, application or dataset involved, testing approach, test scenarios, defects identified, tools used, and outcome.

Communication is also important because the role requires candidates to document findings and communicate with both technical and nontechnical stakeholders.

What Makes This Deloitte Role Different

The provided job description combines several quality engineering disciplines within a single entry-level position. Candidates are expected to understand traditional software testing while also developing knowledge of data validation, analytics testing, API testing, automation, cloud data processes, and AI-enabled applications.

The position therefore provides exposure to both application quality and data quality. This is particularly visible in the requirement to validate reports and dashboards, perform source-to-target comparisons, test ETL/ELT workflows, and examine API and data-pipeline behavior.

The AI and GenAI component is another notable part of the description. The role specifically references response relevance, groundedness, guardrails, retrieval-augmented generation, and response evaluation.

Frequently Asked Questions

What is the Deloitte BTA – Quality Engineer job location?

The position is based in Hyderabad, Telangana, India.

What is the shift timing for this Deloitte Quality Engineer role?

The job description specifies shift timings from 11:00 AM to 8:00 PM.

What educational qualification is required?

The source states that candidates should have a Bachelor’s Degree or equivalent education in Computer Science or a related field.

Is this an entry-level opportunity?

Yes. The position is described as an entry-level Quality Engineer role within the Analytics Horizontal team.

Is SQL required for this position?

The job description specifically mentions basic SQL knowledge for querying, comparing, and validating data, including joins, filters, aggregations, and reconciliation checks.

Does the role involve automation testing?

Yes. The position includes supporting test automation and mentions reusable scripts for API, user-interface, data-validation, and regression testing. Playwright and Selenium are among the tools mentioned in the source.

Does the position involve API testing?

Yes. API testing is included among the testing activities, and Postman is mentioned as an example of an API testing tool.

Does the role involve AI or GenAI testing?

Yes. The job description specifically includes testing AI-enabled applications and mentions areas such as response relevance, groundedness, guardrails, permissions, error handling, retrieval-augmented generation, and responsible use of test data.

Does the source mention a salary?

No salary or compensation figure is provided in the job information supplied here. Candidates should verify compensation details through the official Deloitte recruitment process.

Does the source mention a specific graduation year or percentage requirement?

No specific graduation year or minimum percentage is stated in the provided job description.

What testing tools and technologies are mentioned?

The source mentions Azure DevOps, Jira, Python, C#, JavaScript, Playwright, Selenium, Postman, QlikView, Qlik Sense, SSRS, Bold Reports, Power BI, AWS S3, Glue, Redshift, Lambda, and Databricks, along with SQL, relational databases, REST APIs, data warehouses, ETL/ELT, cloud services, CI/CD, and version control.

Final Thoughts

The Deloitte BTA – Quality Engineer position in Hyderabad is an entry-level opportunity centered on quality engineering for enterprise analytics solutions. The role covers software testing, data validation, SQL, reports and dashboards, APIs, ETL and ELT workflows, automation, Agile delivery, cloud data processes, and AI-enabled applications.

Candidates with a Bachelor’s Degree or equivalent background in Computer Science or a related field can review the opportunity if their interests align with software testing, analytics, data quality, automation, and emerging AI testing practices.

Because the source does not specify every recruitment condition, candidates should verify the latest eligibility requirements, application status, compensation details, and other terms directly through Deloitte's official careers portal before applying.