Senior Automation Engineer

Job Description (JD)

Senior / Lead Automation QA Engineer

Location: Madurai Work Mode: Full-time, On-site Experience: 6+ Years

1. Job Summary

We are seeking a highly skilled and passionate Senior / Lead Automation QA Engineer to join our team at our Madurai office. In this role, you will bridge the gap between traditional UI/API testing, advanced data ecosystem validation, and analytical database benchmarking.

You will lead testing strategies for complex Data Lakes, cloud architectures, and REST APIs while validating workload performance using industry-standard TPC-D and TPC-H benchmarks. Beyond technical execution, you will serve as a framework architect and technical anchor, mentoring junior engineers and fostering a strong culture of data engineering and automation quality.

2. Key Responsibilities

• Framework Architecture & Definition: Architect, implement, and maintain scalable, robust test automation frameworks from scratch for UI, REST APIs, and Big Data/Data Lake verification.
• Analytical Benchmarking (TPC-D / TPC-H): Design and execute data workload simulations using TPC-D and TPC-H benchmark standards to validate decision-support system performance, execution times, and complex business query processing over the Data Lake.
• Data Lake & Cloud Testing: Define and execute validation strategies for large-scale data pipelines, verifying data ingestion, transformations, partitioning, layout optimization, and storage layers within cloud Data Lakes.
• On-Site Technical Leadership & Mentorship: Mentor junior QA team members at the Madurai office. Conduct code reviews, establish coding standards for test scripts, and deliver hands-on training to strengthen the teams automation capabilities.
• End-to-End Automation: Develop high-quality, maintainable, parallel-execution-ready automation scripts using Java across multiple testing layers.
• CI/CD Integration: Integrate automated test suites and benchmark performance assertions into modern DevOps CI/CD pipelines to support stable nightly regressions and quality gates.

3. Technical Requirements & Skills

3.1 Core Automation & Language Skills

• Advanced Java: Strong hands-on proficiency in Java, including Object-Oriented Programming (OOP), Collections, multithreading/concurrency patterns, and exception handling.
• Playwright with Java: Proven experience designing UI automation suites using Playwright with Java, implementing the Page Object Model (POM), and supporting parallel execution.
• REST API Automation: Expert knowledge of RESTful architecture and practical automation experience using REST Assured, Apache HTTP Client, or similar Java-based API clients.

3.2 Data Lake, Query Engines & SQL

• Benchmarking Standards: Comprehensive understanding of TPC-H and TPC-D specification models, decision-support workloads, and ad-hoc query benchmarking metrics.
• Advanced SQL: Ability to write and optimize complex SQL queries involving multi-table joins, window functions, Common Table Expressions (CTEs), and complex aggregations typical of TPC-H suites.
• Distributed Query Engines: Hands-on experience executing, performance-tuning, and debugging queries using Athena and Trino (formerly Presto) across structured and semi-structured datasets such as JSON, Parquet, and Avro.
• Data Lake / Lakehouse: Solid understanding of Data Lakehouse concepts, schema enforcement, data partitioning strategies, and file formats including Parquet, ORC, and Delta Lake.

3.3 Cloud & DevOps Infrastructure

• Cloud Ecosystems: Strong operational understanding of cloud environments, preferably AWS, including S3, IAM, Glue Catalog, and Lambda, and how microservices interact with backend Data Lakes.
• CI/CD Pipelines: Experience integrating automated test frameworks with DevOps tools such as Jenkins, GitHub Actions, GitLab CI, or AWS CodePipeline.

4. Soft Skills & Leadership Qualities

• Framework Definition: Proven ability to assess project requirements and select or build the appropriate testing architecture and technology stack.
• Mentoring & Training: Patience and empathy to explain database benchmarking methodologies and coach junior engineers on clean code and testing best practices.
• Analytical Problem-Solving: Ability to analyze query execution plans, identify database performance degradation, and diagnose data mismatches.

5. Qualifications & Experience

• Experience: 6+ years of core experience in Software Quality Engineering, with a strong focus on automation, API validation, data verification, and database benchmarking.
• Education: Bachelors or Master’s degree in Computer Science, Information Technology, a related engineering discipline, or equivalent practical experience.
• Work Requirements: Willingness to work full-time on-site at the Madurai office.