About the job
Context & Impact
Lansweeper is at the forefront of Asset Intelligence, relying on precision and trustworthiness of data as we expand our capabilities. Following our acquisition of Redjack, we’re enhancing asset visibility through on-premises network sensors. Our mission is to construct scalable and intelligent data pipelines that drive our next generation of insights.
To facilitate this transformation, we are seeking a dedicated Data Quality Automation Engineer to join our Quality Engineering (QE) Team. In this role, you will play a pivotal part in developing automated testing systems for the integrated Data and Machine Learning pipelines of Lansweeper and Redjack. You will collaborate with team members to design comprehensive test plans and conduct product testing, ensuring the integrity and dependability of our offerings.
Your Goals
Establish testing frameworks throughout Redjack’s infrastructure as it integrates with Lansweeper’s architecture.
Develop data quality test frameworks for our combined data pipelines, encompassing both machine learning and analytics.
Automate end-to-end and regression testing within our Continuous Integration/Continuous Deployment (CI/CD) pipelines.
Challenges
You will encounter several challenges, including:
Facilitating seamless integration of Redjack’s data pipelines with Lansweeper’s systems.
Testing network sensor deployments across diverse IT environments.
Scaling automated data quality checks across hybrid data environments.
Incorporating data validation and testing into CI/CD pipelines to ensure model and product reliability.
Key Responsibilities:
Collaborate with the development team to consistently deliver high-quality software to production.
Engage in test planning and cross-team quality assurance efforts for data products.
Maintain and create end-to-end automated test scripts for our CI/CD workflows utilizing platforms such as CircleCI and GitHub Actions. This includes deploying and testing network sensors across various platforms (Linux, Windows) and IT environments (TAP, SPAN, ERSPAN, NETFLOW).
Establish monitoring dashboards, alerts, and anomaly detection pipelines to proactively manage issues.
Document and refine testing strategies continuously to enhance our processes.