Senior SDET Engineer

About the Role

We’re looking for a Senior Software Development Engineer in Test with extensive industry experience to define and execute the design, development, and maintenance of Fivetran’s test automation tools and framework using reliable and scalable techniques.

As a Senior SDET, you will focus on solving complex testing difficulties by designing, developing and improving automation and reporting frameworks. You will invest in improving test stability and performance of the framework by developing innovative solutions to boost Fivetran’s testing efficiency. You will also coach Fivetran quality engineers to be best-in-class automation engineers, and will continuously work with the team to ensure high standards for automation. The ideal candidate will be highly technical, detail-oriented, creative, motivated, and focused on achieving results.

This is a full-time position based out of our Bangalore office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team.

Technologies You’ll Use

• Java 11, JUnit 5
• Datalakes and Catalog technologies
• Docker and Kubernetes
• AWS, GCP, Azure
• WireMock
• Bazel, Buildkite

What You’ll Do

• Review requirements, specifications and technical design documents to provide meaningful, risk-focused feedback.
• Design and evolve scalable automation frameworks in Java with a strong emphasis on reliability, performance, and data correctness.
• Build the datalakes team’s automation suite from the ground up, establishing the foundations, patterns, and best practices for scalable and maintainable test automation.
• Write high-signal test strategies for complex features and automate them across multiple environments.
• Improve CI/CD pipelines by building robust validation layers that prevent silent failures and regressions.
• Build internal tools and proof-of-concepts to improve engineering productivity, including areas such as:
  • Faster debugging and failure triagingi
  • Improved test scenario generation
  • Flaky test detection
  • Better log analysis and root-cause identification
• Use modern engineering tools, including basic AI-assisted tooling where appropriate, to improve development and testing workflows.
• Actively measure and improve engineering impact through reliability metrics, automation efficiency, and defect prevention signals.
• Collaborate with engineering teams to drive a culture of quality ownership and automation-first thinking.

Skills We’re Looking For

• 5+ years of experience in the software industry with a strong passion for quality, automation, and engineering excellence.
• Strong proficiency in Java and a deep understanding of object-oriented programming principles.
• Experience designing scalable automation frameworks and identifying negative, edge, and high-risk scenarios.
• Strong understanding of distributed systems risks such as schema drift, idempotency failures, data inconsistencies, and race conditions.
• Hands-on experience with cloud platforms such as AWS, GCP, or Azure, and containerized environments such as Docker and Kubernetes.
• Experience building and maintaining CI/CD pipelines using tools such as Jenkins, CircleCI, or Buildkite.
• Experience working with backend automation frameworks.
• Knowledge of database testing and ETL or data pipeline validation is a strong plus.

AI & Productivity Engineering

• Basic familiarity with AI-assisted developer tools and productivity workflows.
• Ability to use AI tools effectively for tasks such as debugging, test design, documentation, or log analysis, with appropriate validation of outputs.
• Good judgment in verifying generated results and maintaining quality, reliability, and safety in engineering workflows.
• Interest in using modern tooling to improve engineering productivity and effectiveness.

Datalakes

• Exposure to datalake technologies and concepts such as object storage, file-based table formats, metadata management, and large-scale data processing workflows.
• Familiarity with testing data movement, schema evolution, partitioning, and data correctness in datalake environments is a plus.

#LI-HYBRID #LI-PE1