[Hiring] Data Engineer @Volis AI

Role Description

As a Data Engineer at Volis, you will play a key role in building and maintaining scalable, reliable, and efficient data architectures. You will have the opportunity to:

• Deliver high-impact solutions with Palantir Foundry:
  • Work hands-on with Palantir Foundry to build end-to-end data solutions — from ingestion and modeling to analytics and operational use cases — supporting complex, business-critical projects for large organizations.
• Work with cutting-edge technologies:
  • Utilize modern tools such as Airflow, Airbyte, dbt, BigQuery, Terraform, Kubernetes, Docker, and cloud environments.
• Ensure data reliability and scalability:
  • Develop monitoring, testing, and alerting strategies to guarantee data integrity and performance at scale.
• Collaborate across teams:
  • Work closely with analysts, data scientists, and business stakeholders to understand data needs and deliver high-impact solutions.
• Promote best practices:
  • Help define and implement data engineering standards, ensuring code quality and documentation through GitHub workflows.

Qualifications

• Solid experience as a Data Engineer or in similar roles, with a proven track record of designing and implementing data pipelines and architectures.
• Strong skills in SQL (preferably BigQuery), Python, Airflow, dbt and experience with infrastructure tools like Terraform, Docker, and Kubernetes.
• Solid knowledge in software development and its best practices is very important.
• Experience working with cloud platforms (preferably GCP).
• Proactivity, autonomy, and a strong sense of responsibility to solve complex data challenges.
• Ability to deliver high-quality solutions on time, aligned with business goals, evaluating different possibilities and comparing trade-offs.
• Eagerness to explore new technologies and improve your skills.
• Fluency in English is essential, as we have English-speaking clients.

Requirements

• Previous experience delivering complex data solutions using Palantir Foundry for large organizations, with a strong consulting mindset and focus on translating business problems into scalable data products.
• Experience with MLOps tools and processes (e.g., MLflow, Kubeflow, Vertex AI).
• Experience with data streaming architectures and/or real-time data processing.
• Master's degree in a technical or analytical field.

Benefits

• Collaborative, remote culture with the opportunity to grow with the company.
• Participate in the creation of a rapidly growing data startup. Help define best practices, processes, and learn by experience.
• Chance to work with large companies in real estate, highway management, construction, and more.