Senior Data Engineer - Databricks and Snowflake

We are seeking a Senior Data Engineer for an ongoing Life Science project to be engaged in building data pipelines and leveraging cloud technologies.

Location:

Quantori is an international team: we have colleagues who work not only from office but also remotely from all over the world.

Responsibilities:

• Design, build, and maintain scalable data pipelines for acquiring, integrating, and managing data from diverse data generation sources and systems (e.g., lab systems, MES, clinical supply, quality systems, external partners).
• 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, implementing enterprise-level data models, and creating new models as needed.
• Enable AI/ML readiness by ensuring data is well-structured, versioned, traceable, and semantically aligned with enterprise data standards.

What we expect:

• Bachelor’s degree in Engineering, Data Science, Life Sciences, Computer Science, or related field; advanced degree preferred.
• 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 (AWS services, Snowflake, Databricks, Redshift) along with Spark and dbt.
• Proficiency in RDS
• Expertise in ETL and DWH.
• Experience with NoSQL and graph databases.
• English language proficiency of B2+
• Strong analytical, problem-solving, and stakeholder-management skills, with the ability to translate discussions into actionable requirements.
• Ability to drive multiple exciting projects simultaneously with strong organizational skills and adaptability.

Nice to have:

• Experience working with the histopathology domain
• 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 (e.g., imaging, sensor data, etc).
• 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.

We offer:

• Competitive compensation
• Fully remote work
• Flexible working hours
• Continuous education, mentoring, and professional development programs
• A team with an excellent tech expertise