Data Quality Automation Engineer
Role details
Job location
Tech stack
Job description
To accelerate this transformation, we're hiring a Data Quality Engineer within our Quality Engineering (QE) Team. You'll help build out automated test systems for Lansweeper's and Redjack's integrated Data/ML pipelines, design test plans alongside the team and help test the product, ensuring integrity and reliability., * Implement test frameworks across RedJack's infrastructure as it integrates with Lansweeper's architecture.
- Implement data quality test frameworks across combined data pipelines (ML and analytics).
- Automated e2e & regression testing within CI/CD pipelines.
Challenge
The main challenges you'll face are:
- Ensuring smooth integration of Redjack's data pipelines with Lansweeper's systems.
- Testing deployments of network sensors to a variety of IT environments.
- Scaling automated data quality checks across hybrid data environments.
- Embedding data validation and testing into CI/CD pipelines to safeguard model and product reliability., * Work with the development team to continuously deliver high quality software to production.
- Participate in test planning and cross-team QA efforts for data products.
- Maintain and write e2e automated test scripts for our CI/CD workflows (CircleCI, Github actions, etc) Deploying and testing Network sensors to various platforms (Linux, Windows, etc) and various IT environments (TAP, SPAN, ERSPAN, NETFLOW, etc)
- Set up monitoring dashboards, alerts, and anomaly detection pipelines for proactive issue management.
- Document and evolve testing strategies for data validation, profiling, and pipeline reliability.
- Design and implement automated data quality test plans for structured and unstructured data within machine learning pipelines.
Requirements
- 4+ years in Quality Engineering, Data Quality, or ML Test Automation roles.
- Strong proficiency in Python and SQL for building validation and monitoring tools.
- Skilled in automating tests within CI/CD (Airflow, Kubeflow, MLflow, Github Actions).
- Experience with data quality frameworks (Great Expectations, dbt, Apache Deequ).
- Experience in testing distributed systems (API validation, Kafka, etc).
- Experience with cloud-based data infrastructure (Snowflake, BigQuery, AWS S3).
Nice to Haves:
- Experience with Rust.
- Familiarity with mocking libraries (Mockito, mountebank, etc).
- Familiarity with Docker & Kubernetes.
- Familiarity with Networking concepts.
- Experience in AWS, GCP, and Azure
Soft Skills:
- Analytical mindset with strong problem-solving capability.
- Excellent communication and cross-team collaboration.
- Detail-oriented, structured, and committed to continuous improvement.
Benefits & conditions
- Competitive salary according to industry benchmarks.
- Benefits: comprehensive health insurance, meal vouchers, pension plan, company car, Flexible Income Plan, phone subscripion…
- Career growth & learning opportunities within a fast-scaling SaaS company.
- Flexibility in working hours and hybrid work options.
- Engaging company culture with team events and international collaboration
Company Info
Lansweeper is the Technology Asset Intelligence platform that transforms raw asset data into trusted, actionable insights - spanning hardware, software, cloud, IoT, and OT.
With a single solution, organizations gain full visibility across their technology estate, empowering IT, security, operations, and finance teams to make smarter, faster decisions.
We help our customers:
- Tame hybrid infrastructures
- Manage compliance risks
- Reduce complexity by delivering timely, accurate visibility and seamless integration into their ecosystems
From universal asset discovery to AI-powered intelligence, Lansweeper delivers clarity and confidence to organizations worldwide.