AES - Delivery - Digital Test Automation Engineer

Zensar Technologies; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Zensar Technologies seeks an experienced QA engineer to own quality across data pipelines, microservices, APIs, GUIs, and LLM/ML integrations on Databricks and Azure. You will drive test strategy, design and execute tests, automate where possible, and manage tickets in Azure DevOps or Jira.

The role emphasizes agentic QA for LLM workflows, contract and integration tests, and regression coverage with a focus on data integrity and pricing rules.

Qualifications

• 5+ years of QA, software testing, or related roles.
• Hands-on experience validating Databricks pipelines, Delta Lake, and Spark outputs.
• Medium proficiency in T-SQL for validation queries and database testing.
• Experience with Azure Data Factory, ADLS/Blob Storage, and Azure Functions.
• Strong API testing experience with REST APIs, Postman, and OpenAPI/Swagger.
• GUI testing using Selenium/Playwright; exploratory testing.
• Familiarity with containerized microservices, messaging, and orchestration.
• Understanding of ML lifecycle, prompt engineering basics, and LLM evaluation.
• Concepts of agentic QA, safety checks, and evaluation metrics.

Responsibilities

• Define and maintain QA strategy for data, API, GUI, microservices, and LLM features.
• Create reusable test cases for functional, integration, regression, and performance testing.
• Validate ETL/ELT pipelines and data accuracy in Databricks and Delta Lake.
• Design and run contract, integration, and negative tests for RESTful APIs.
• Develop UI test plans and automate tests using Selenium/Playwright.
• Test service contracts, message flows, and backward compatibility in microservices.
• Design evaluation metrics and test harnesses for ML models and LLM integrations.
• Create minimal prompts and agentic QA processes for autonomous agents.
• Automate tests and integrate into CI/CD; manage defects in Azure DevOps or Jira.

Skills

Analytical thinking

Clear communication

Cross-team collaboration

Tools

Databricks

Delta Lake

Spark

T-SQL

Postman

OpenAPI/Swagger

Selenium

Playwright

Azure DevOps

Jira

Job description

Job Description

You will own quality for data pipelines, microservices, APIs, GUIs, and LLM/ML integrations running on Databricks and Microsoft Azure. The role focuses on test strategy, test case design and execution, automation, ticket management, and agentic QA for LLM workflows. Minimum experience: 5 years

Job Description

You will own quality for data pipelines, microservices, APIs, GUIs, and LLM/ML integrations running on Databricks and Microsoft Azure. The role focuses on test strategy, test case design and execution, automation, ticket management, and agentic QA for LLM workflows. Minimum experience: 5 years

Responsibilities

• Key Responsibilities
• Test Strategy and Planning
• Define and maintain QA strategy for data, API, GUI, microservices, and LLM/ML features; prioritize test coverage based on risk and business impact.
• Test Case Design and Execution
• Create clear, reusable test cases for functional, integration, regression, performance, and pricing scenarios; execute manual and automated tests and maintain test artifacts.
• Data and Database Testing
• Validate ETL/ELT pipelines on Databricks and Delta Lake; write and run T‑SQL validation queries; verify data lineage, completeness, and correctness.
• API Testing
• Design and run contract, integration, and negative tests for RESTful APIs; use Postman, OpenAPI/Swagger, and automated API test suites.
• GUI Testing
• Create and execute UI test plans for web applications; perform exploratory testing and maintain automated UI tests using Selenium, Playwright, or equivalent.
• Microservices Validation
• Test service contracts, message flows, resilience, and backward compatibility across containerized microservices; validate observability and error handling.
• LLM and ML QA
• Design evaluation metrics and test harnesses for ML models and LLM integrations; validate inference correctness, hallucination rates, latency, and cost tradeoffs.
• Prompt Engineering and Agentic QA
• Create minimalistic, cost‑aware prompts and prompt templates; implement agentic QA processes for autonomous agents including safety checks, guardrails, and evaluation pipelines.
• Pricing and Business Logic Testing
• Validate pricing engines, discount rules, billing flows, and edge cases; create scenario matrices and automated checks for pricing correctness.
• Automation and CI/CD
• Integrate tests into CI/CD pipelines; author automated test suites, test runners, and validation scripts; collaborate with SRE/DevOps on test environments.
• Ticketing and Incident Management
• Raise, triage, and manage tickets in Azure DevOps or Jira; document reproduction steps, root cause analysis, and remediation.
• Documentation and Collaboration
• Produce test plans, runbooks, release checklists, and postmortems; mentor junior QA engineers and participate in cross‑functional reviews.

Required Skills And Experience

Experience: Minimum 5 years in QA, software testing, or related roles.

Databricks and Data Testing: Hands‑on experience validating Databricks pipelines, Delta Lake, and Spark outputs.

Microsoft SQL Server: Medium proficiency in T‑SQL for validation queries and database testing.

Azure: Practical experience with Azure Data Factory, ADLS/Blob Storage, Azure DevOps, and Azure Functions.

API Testing: Strong experience with REST APIs, Postman, OpenAPI/Swagger, and automated API testing.

GUI Testing: Experience with Selenium, Playwright, or equivalent UI automation tools and exploratory testing.

Microservices: Familiarity testing containerized services, message queues, and service orchestration.

LLM and ML Fundamentals: Understanding of ML lifecycle, model evaluation, prompt engineering basics, and LLM failure modes.

Prompt Engineering: Ability to craft minimalistic prompts and maintain prompt libraries for reproducible tests.

Agentic QA Awareness: Knowledge of agentic QA concepts, safety checks, and evaluation metrics for autonomous agents.

Testing Tools and Automation: Experience with test frameworks, CI/CD integration, and test data management.

Ticketing Tools: Experience using Azure DevOps, Jira, or similar.

Soft Skills: Strong analytical thinking, clear written communication, and cross‑team collaboration.

Nice to Have

Certifications: ISTQB, Azure Data Engineer, or Databricks certifications.

Programming: Python for test automation and data validation; familiarity with Scala or Java.

Observability: Experience with Application Insights, Datadog, Prometheus, or Grafana.

Performance Testing: Experience with JMeter, k6, or similar tools.

LLM Ops: Experience with prompt versioning, cost monitoring, and model evaluation frameworks.

Infrastructure as Code: Familiarity with Terraform or ARM templates for test environment provisioning.

Qualifications

• Key Responsibilities
• Test Strategy and Planning
• Define and maintain QA strategy for data, API, GUI, microservices, and LLM/ML features; prioritize test coverage based on risk and business impact.
• Test Case Design and Execution
• Create clear, reusable test cases for functional, integration, regression, performance, and pricing scenarios; execute manual and automated tests and maintain test artifacts.
• Data and Database Testing
• Validate ETL/ELT pipelines on Databricks and Delta Lake; write and run T‑SQL validation queries; verify data lineage, completeness, and correctness.
• API Testing
• Design and run contract, integration, and negative tests for RESTful APIs; use Postman, OpenAPI/Swagger, and automated API test suites.
• GUI Testing
• Create and execute UI test plans for web applications; perform exploratory testing and maintain automated UI tests using Selenium, Playwright, or equivalent.
• Microservices Validation
• Test service contracts, message flows, resilience, and backward compatibility across containerized microservices; validate observability and error handling.
• LLM and ML QA
• Design evaluation metrics and test harnesses for ML models and LLM integrations; validate inference correctness, hallucination rates, latency, and cost tradeoffs.
• Prompt Engineering and Agentic QA
• Create minimalistic, cost‑aware prompts and prompt templates; implement agentic QA processes for autonomous agents including safety checks, guardrails, and evaluation pipelines.
• Pricing and Business Logic Testing
• Validate pricing engines, discount rules, billing flows, and edge cases; create scenario matrices and automated checks for pricing correctness.
• Automation and CI/CD
• Integrate tests into CI/CD pipelines; author automated test suites, test runners, and validation scripts; collaborate with SRE/DevOps on test environments.
• Ticketing and Incident Management
• Raise, triage, and manage tickets in Azure DevOps or Jira; document reproduction steps, root cause analysis, and remediation.
• Documentation and Collaboration
• Produce test plans, runbooks, release checklists, and postmortems; mentor junior QA engineers and participate in cross‑functional reviews.

Interview and Evaluation Guide

Technical screen: SQL validation problem and API testing scenarios.

Practical exercise: Create test cases and automated checks for a sample Databricks ETL and an API that returns pricing.

LLM prompt exercise: Provide minimal prompts for a given LLM task and design evaluation metrics for correctness and safety.

System design: Design an agentic QA pipeline for autonomous agents including test harness, safety gates, and monitoring.

Behavioral: Examples of ticket triage, incident postmortems, and cross‑team collaboration.

Success Criteria at 6 Months

• Test Coverage: Comprehensive, automated test suites for data pipelines, APIs, and core GUI flows.
• LLM Readiness: Reproducible prompt templates, evaluation metrics, and agentic QA checks integrated into CI.
• Reliability: Reduced production incidents and faster mean time to resolution through clear runbooks and test automation.
• Pricing Confidence: End‑to‑end validated pricing flows with scenario tests and regression guards.
• Collaboration: Trusted QA partner to engineering and product teams with documented processes and mentoring outcomes.

About Us

At Zensar, we’re "experience-led everything". We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: "Together, we shape experiences for better futures". Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is "ONE with Client" - a set of four core values that reflect who we are and how we work: "One Zensar, Nurturing, Empowering, and Client Focus".

Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.

We believe the best work happens when individuality is celebrated, growth is encouraged, and well‑being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.