Lead Quality Engineer- Python, SQL

Job Summary

As a Lead Quality Engineer, you will be responsible for driving quality across complex, datarich applications by designing robust test strategies, building automated testing frameworks, improving test coverage, and partnering closely with developers, product managers, and designers. You will contribute to quality engineering best practices and ensure the successful delivery of missioncritical solutions.

Responsibilities Quality Engineering Automation

Design, develop, and maintain automated test frameworks and test suites (UI, API, data validation, performance). Build automation using Python as a primary scripting and test development language. Implement automated tests for REST/GraphQL APIs, microservices, and data pipelines. Ensure robust test coverage across functional, regression, integration, performance, and security testing.

Data Quality Validation

Validate highvolume datasets, transformations, ingestion pipelines, and data models. Create automated data quality checks, anomaly detection rules, and validation scripts. Work alongside data engineering teams to validate ETL workflows, schema changes, and downstream impacts.

Collaboration Agile Delivery

Partner with developers, product managers, and designers to understand requirements and acceptance criteria. Participate in backlog refinement, design discussions, sprint planning, and daily standups. Contribute to documentation, QE best practices, process improvements, and quality metrics. Support release readiness and production validation activities.

What We're Looking For Basic Qualifications

• Bachelors or masters degree in computer science, Information Systems, Engineering, or equivalent.
• 8+ years of handson Quality Engineering experience, including test automation frameworks and tooling.
• Strong expertise in:
  • Python coding and scripting
  • API testing (REST/GraphQL)
  • Test automation tools (PyTest, Robot, Playwright/Selenium, Postman, etc.)
  • SQL NoSQL databases
  • Cloud environments (AWS, Azure, or GCP)
  • CI/CD pipelines (Git, GitHub Actions, Azure DevOps, Jenkins, etc.)
• Experience validating microservices, distributed systems, and data workflows.
• Strong understanding of SDLC, Agile methodology, and testdriven development principles.
• Ability to collaborate effectively with crossfunctional teams and contribute to architectural and design discussions from a quality perspective.

Preferred Qualifications

• Experience in performance testing (JMeter, Locust, k6).
• Experience with data platforms such as Snowflake, Databricks, or BigQuery.
• Familiarity with React/Node.js application testing (Playwright, Cypress).
• Exposure to Energy Transition or Energy Markets is a plus.
• Enthusiasm for Data Science, MLdriven testing, or model validation is an added advantage.