Company Overview
aivontis is an AI-native venture studio focused on building high-impact platforms for healthcare and life sciences. We believe AI should not be an add-on but the foundation of every solution. Our mission is to solve real-world healthcare challenges by embedding intelligence into the core of diagnosis, drug discovery, clinical operations, and decision systems. Our vision is to accelerate healthcare outcomes through intelligent systems that are fast, scalable, and built for complexity.
The Team
Our data engineering team is responsible for building the infrastructure that powers intelligent systems across aivontis products such as Synapse and Circulus. This team manages large volumes of sensitive and diverse data, builds real-time and batch processing pipelines, and enables advanced analytics and machine learning workflows. We work closely with our product, design, and AI research teams to ensure our solutions are reliable, secure, and truly scalable in real-world healthcare environments.
Key Responsibilities
- Develop and maintain robust data pipelines that handle large structured and unstructured datasets.
- Work with cross-functional teams to translate data requirements into effective solutions.
- Ensure high standards of data quality, validation, and compliance.
- Build scalable data infrastructure for both real-time and batch processing.
- Integrate third-party data sources and APIs, enabling seamless information flow across platforms.
- Support data governance and documentation practices for audit readiness and traceability.
- Contribute to the technical design and architecture of data platforms across different aivontis ventures.
Qualifications and Skills
- Minimum of 3 years of experience in data engineering or related fields.
- Proficiency in Python, SQL, and experience with distributed systems such as Apache Spark or Flink.
- Experience working with cloud platforms such as AWS or Google Cloud.
- Strong understanding of ETL processes, data warehousing, and pipeline orchestration tools.
- Familiarity with tools like Kafka, Airflow, Databricks, or similar platforms.
- Knowledge of data privacy and security practices in regulated domains such as healthcare is preferred.
- Ability to work in a fast-paced, iterative environment with a strong focus on real-world impact.
What We Look For
- A structured thinker with strong problem-solving skills.
- A team player who communicates clearly and collaborates effectively.
- A proactive mindset with a willingness to work on both strategy and execution.
- Commitment to building systems that contribute meaningfully to better health outcomes.