Test Engineer (For temp workers)

The Trips Data Finance team is responsible for providing accurate and timely financial data from multiple sources across the business to our Enterprise Resource Planning (SAP) platform and other critical financial processes.

As a Test Engineer - Data, you will work with data-producing teams in the Trips Business Unit to improve the quality, reliability and trustworthiness of data products and financial data flows. You will partner with engineers, product managers and finance stakeholders in domains such as Trips Data Finance, where we provide accurate and timely financial data from multiple sources into our platform and other critical financial processes.

You will help teams design and implement effective validation for data pipelines, APIs and services, ensuring that data is correct, complete and timely, and that failures are surfaced early. We are looking for a proactive test engineer and strong communicator who can coach teams on data testing practices, set a strong testing strategy in the  team, in line with the Booking.com Quality Strategy. and help teams take real ownership of their testing and quality outcomes.

Key Responsibilities and Duties

Testability

• Work directly with teams to improve their quality maturity in line with the Booking.com Quality Strategy, focusing on data pipelines, services and financial data flows.

  
  

• Embed testability in Definition of Ready/Done, including documented evidence and regular review of quality and observability metrics.

  
  

• Apply and operationalise requirements from regulated environments (e.g. SOX, GDPR/PII, DMA) in day-to-day work, ensuring they are reflected in test strategy, coverage and documentation.

  
  

• Introduce and support test tools for data quality, contract testing, automation, observability, experimentation and feature flagging.

  
  

• Drive observability using monitoring, alerts, dashboards, canaries and experiments to validate behaviour and data quality in production.

  
  

• Increase decomposability by promoting isolated component tests before end‑to‑end validation.

  
  

• Improve system controllability via clear inputs, configurations and test data to enable  running scenarios consistently across environments.

  
  

• Define effective test environments (dev, test, pre‑prod, prod) with realistic, compliant data and stable infrastructure.

  
  

Test Advocacy

• Test with the team, not for the team coaching engineers so they understand and own the testing and quality checks of their products.

  
  

• Use strong written and verbal communication to explain testing concepts to technical and non-technical audiences, and to influence across teams and verticals.

  
  

Automation

• Design and evolve test approaches that cover appropriate levels (unit, component, contract, integration, end-to-end, data checks) and favour fast feedback loops.

  
  

• Ensure that validation is integrated into CI/CD pipelines and that failures prevent deployments when data quality is at risk.

  
  

• Advocate for and help teams adopt appropriate tools and frameworks (e.g. test automation frameworks, contract testing, data quality tooling, experimentation platforms and feature flagging) to improve coverage and confidence.

  
  

• Use surrounding technologies such as Git, CI/CD pipelines, Docker, Kubernetes and AWS to enable reliable and efficient automation.

  
  

• Design and maintain realistic mocks and stubs for upstream and downstream systems, keeping contracts aligned with production behaviour.

  
  

Data

• Work closely with teams building data or backend systems (e.g. data pipelines, financial data feeds, APIs integrating with SAP or reporting platforms) to ensure robust test strategies and coverage.

  
  

• Define and implement data validation for accuracy, completeness and timeliness, including:

  
  

• Schema and contract checks.

  
  

• Reconciliation of data across systems.

  
  

• Transformation validation for data feeding SAP and other finance systems.

  
  

• Use relational databases, ideally Microsoft SQL Server, including writing and optimising SQL for test design, data setup and investigation of data issues.

  
  

Non-functional Requirements and Quality Controls

• Maintain test evidence, documentation and observability so that quality controls for SOX, GDPR/PII and DMA can be demonstrated to internal and external auditors.

  
  

• Use and interpret quality metrics (e.g. Change Failure Rate, Lead Time to Change, Mean Time to Mitigate, Defect Age) to identify, prioritise and track quality improvements for services and data products.

  
  

• Design and validate observability (logs, metrics, traces, alerts, dashboards) for data systems and financial data flows.

  
  

Qualifications & Skills

• Experience testing data-intensive or backend systems, such as:

  
  

• Data pipelines and ETL/ELT processes.

  
  

• Financial data feeds.

  
  

• APIs integrating with SAP or reporting platforms.

  
  

• Experience working with or around relational databases, ideally Microsoft SQL Server, including writing and optimising SQL for test design and data investigation.

  
  

• Experience with modern engineering tooling and environments, such as uch as Git, CI/CD pipelines, Docker, Kubernetes and AWS (or similar cloud platforms) is an advantage.

• Experience working in or around regulated environments (e.g. SOX, GDPR/PII, DMA), or a strong willingness to learn and apply these requirements in everyday work.

  
  

• Proven ability to raise a team’s testing maturity through pairing/mobbing, workshops, coaching and facilitation.

  
  

• Strong communication skills, both written and spoken, with the ability to explain testing and data quality concepts to technical and non-technical audiences and to influence across teams and verticals.

  
  

• Use structured problem‑solving (root‑cause analysis, “5 whys”) to debug complex issues.