Machine Learning & Data Engineer

• Identify, evaluate, and integrate modern AI technologies into our stack.
• Connect raw data and develop scalable ETL/ELT workflows in Databricks.
• Design, test, and operate CI/CD pipelines using GitHub Actions and Databricks Jobs.
• Deploy ML and GenAI microservices, optimizing for latency and scalability with monitoring and alerting.
• Identify AI potential in business processes, prioritize opportunities, and translate them into value-generating use cases.
• Develop, validate, and continuously improve forecasting models, machine learning algorithms and statistical analyses.
• Clearly document and communicate methods, results and insights for both technical and business stakeholders.
• Collaborate closely with our Data Scientist in tech sparring sessions, sharing code reviews, architectural decisions and best practices.

• Proven hands-on experience as a Data Engineer and Machine Learning Engineer in production-grade projects.
• Deep knowledge of Python and SQL for data preparation, modeling, and analysis.
• Initial practical experience with Databricks.
• Confident in working with CI/CD pipelines for testing, packaging, and deployment.
• Familiarity with DBT for structuring and automating ETL/ELT processes.
• Experience with common machine learning algorithms, statistical analysis, and forecasting models.
• Strong problem-solving skills and a sharp eye for detail.
• Excellent communication and teamwork skills.
• Ability to manage multiple projects and priorities in a structured and organized manner.

• Flexible Working Hours
• Workation
• Professional Development
• Job bicycle
• Events
• Discounts
• Company Car
• Dogs Allowed
• Free beverages
• Permanent contract
• Part-Time
• Mobile Phone
• Well-Connected by Public Transport
• Parking

How do you stay relevant in a world that’s constantly changing? What does it take to build long-term business success? These are the questions we’re focused on.

vengine supports companies in the construction machinery trade and industry through their digital transformation – strategically, pragmatically, and with a deep understanding of processes, people, and technologies.