data engineer for scientific data

Quantori is an international team that develops custom software solutions enabling advanced analytics and digital process transformation across scientific, technical, and operational domains.

• Design, build, and maintain scalable data pipelines for acquiring, integrating, and managing data from diverse data generation sources and systems;
• Create and optimize data flows for structured and unstructured data using Python (PySpark), R, SQL, Databricks, Snowflake, and other modern engineering tools;
• Develop and maintain specific data repositories;
• Implement enterprise-level data models and create new models as needed;
• Enable AI/ML readiness by ensuring data is well-structured, versioned, traceable, and semantically aligned with enterprise data standards.

• Bachelor’s degree in Engineering, Data Science, Life Sciences, Computer Science, or a related field;
• 6+ Years of experience in data engineering, including data modeling and database design, preferably in a scientific, manufacturing, or healthcare environment;
• Proficiency with Python, R, SQL, and cloud-based architectures, including AWS services, Snowflake, Databricks, Redshift, Spark, and dbt;
• Familiarity with Databricks AI/BI, Tableau, or other BI tools;
• Expertise in ETL and DWH;
• Experience with NoSQL and graph databases;
• English language proficiency of B2+;
• Strong analytical, problem-solving, stakeholder-management, organizational, and adaptability skills;
• Ability to translate discussions into actionable requirements;
• Ability to drive multiple projects simultaneously;
• Nice to have: experience with regulated or standards-driven data environments such as CDISC, HL7, FHIR, OMOP, DICOM, or manufacturing/quality data standards, familiarity with high-dimensional data, experience with principles connecting to or feeding MLOps and model deployment workflows, knowledge of manufacturing systems (MES), laboratory information systems, or industrial data systems, exposure to knowledge graph or ontology-driven architectures.

• Competitive compensation;
• Flexible working hours;
• Continuous education, mentoring, and professional development programs;
• A team with excellent tech expertise.