Senior Software Engineer Automation

Senior Software Engineer – Automation (Data Engineering | Python | BigQuery)

Overview

Sabre is the global leader in innovative technology that leads the travel industry. We are always looking for talented and driven engineers who are passionate about building scalable, cloud-native software solutions. If you enjoy solving complex technical problems, working with modern cloud technologies, and collaborating in Agile teams to deliver high-quality products—then Sabre is the place for you.

We are seeking a Senior Software Engineer – Automation with 6–8 years of experience in backend and data engineering test automation. This role is ideal for an experienced automation engineer who has strong expertise in Python, PySpark, and BigQuery, and a deep understanding of data validation, ETL testing, and large-scale data platform quality engineering.

While the role includes some UI automation using Playwright, it is predominantly focused on backend, API, and data pipeline automation. The ideal candidate should have strong programming skills, solid SQL expertise (especially BigQuery), and experience validating complex data engineering workflows in cloud environments.

You will work closely with Data Engineers, Backend Engineers, Product Managers, and DevOps teams to ensure high data quality, reliability, scalability, and performance of modern data platforms.

Responsibilities

Automation Strategy & Framework Development

• Design, develop, and maintain robust automation frameworks for backend systems and data pipelines.
• Build scalable automation solutions using Python and PySpark for validating large datasets.
• Develop automated validation suites for ETL/ELT pipelines and data transformations.
• Create reusable libraries for data quality checks, schema validation, reconciliation, and regression testing.
• Define automation best practices for data engineering quality assurance.
  
  

• Write complex SQL queries in BigQuery for data validation, transformation verification, and reconciliation.
• Validate data ingestion, transformation, aggregation, and reporting layers.
• Perform large-scale data comparisons across systems and environments.
• Ensure correctness of partitioned tables, clustered tables, and performance-optimized queries.
• Validate data quality metrics such as completeness, consistency, accuracy, and timeliness.
• Optimize test queries for performance and cost efficiency in BigQuery.
  
  

• Automate REST API testing using Python-based frameworks.
• Validate business logic, data contracts, and service integrations.
• Perform contract testing and integration testing for distributed systems.
• Implement end-to-end automated regression suites for backend services.
  
  

• Develop and maintain UI automation scripts using Playwright.
• Automate critical user journeys and data-driven UI validation scenarios.
• Integrate UI tests into CI/CD pipelines.
• Ensure cross-browser automation coverage where required.
  
  

• Integrate automation suites into CI/CD pipelines.
• Enable automated test execution for pull requests, releases, and scheduled runs.
• Work with DevOps teams to ensure reliable test environments and test data management.
• Monitor automation results and improve test stability and coverage.
  
  

• Participate in requirement reviews to identify test scenarios early.
• Collaborate with Data Engineers to validate complex transformations and business rules.
• Mentor junior engineers on automation best practices.
• Contribute to continuous improvement of automation standards, tooling, and processes.
  
  

• 6–8 years of experience in software engineering with a strong focus on automation.
• Proven experience in backend and data engineering automation.
  
  

• Strong programming expertise in Python.
• Hands-on experience with PySpark for data validation and large-scale dataset testing.
• Deep expertise in Google BigQuery, including:
• Complex SQL queries
• Data modeling validation
• Query optimization
• Partitioning and clustering concepts
• Experience validating ETL/ELT data pipelines.
• Strong understanding of data warehousing concepts and distributed data processing.
• Experience in API automation and backend testing frameworks.
• Experience with Playwright for UI automation.
• Familiarity with Git-based version control systems.
  

• Experience working in cloud environments (preferably GCP).
• Understanding of cloud-based data architectures.
• Familiarity with CI/CD pipelines and automated test execution.
• Experience working with containerized environments is a plus.
  
  

• Strong understanding of test design principles and automation patterns.
• Experience in data reconciliation, schema validation, and data quality frameworks.
• Ability to design scalable and maintainable automation frameworks.
• Strong debugging and root cause analysis skills.
  
  

• Strong analytical and problem-solving skills.
• Excellent communication skills and ability to work in cross-functional teams.
• Ability to take ownership of quality outcomes.
• Proactive mindset toward improving automation maturity and coverage.
  
  

• Bachelor’s Degree in Computer Science, Engineering, or related field (required).
• Master’s Degree in Computer Science or related field (preferred).
• Experience working in high-scale data platforms or enterprise-grade systems is strongly preferred