Senior R&D Data Engineer (Life Sciences)

TL;DR

Senior R&D Data Engineer (Life Sciences): Design, build, and maintain scalable data pipelines for acquiring, integrating, and managing data from lab systems, MES, clinical, and quality sources with an accent on AI/ML readiness, data modeling, and semantic alignment. Focus on optimizing data flows with PySpark, SQL, Databricks, Snowflake, implementing versioning, lineage tracking, and partnering with data scientists on enterprise architectures.

Location: Remote from all over the world or office work

Company

International team specializing in digital transformation for scientific, manufacturing, and healthcare environments.

What you will do

• Design, build, and maintain scalable data pipelines for diverse sources using Python (PySpark), R, SQL, Databricks, Snowflake.
• Develop data repositories, enterprise-level models, and ensure AI/ML readiness with structured, versioned, traceable data.
• Partner with data scientists, domain experts, and ontology teams to translate needs into data products and architectures.
• Implement data quality standards, KPIs, versioning, lineage for compliance and performance.
• Collaborate cross-functionally with stakeholders to design solutions and drive adoption across multiple projects.

Requirements

• Bachelor’s degree in Engineering, Data Science, Life Sciences, Computer Science or related; advanced degree preferred.
• 3+ years in data engineering, data modeling, database design, preferably in scientific/manufacturing/healthcare.
• Proficiency with Python, R, SQL, cloud architectures (AWS, Snowflake, Databricks, Redshift).
• Expertise in ETL, DWH, NoSQL, graph databases.
• English: B2+ proficiency
• Strong analytical, problem-solving, stakeholder-management, organizational skills.

Nice to have

• Experience with regulated data standards (CDISC, HL7, FHIR, OMOP, DICOM, manufacturing/quality).
• Familiarity with high-dimensional data (imaging, sensors).
• Knowledge of MLOps, model deployment, MES, lab systems, knowledge graphs/ontologies.

Culture & Benefits

• Competitive compensation.
• Remote or office work with flexible hours.
• Healthcare: medical insurance, paid sick leave.
• Continuous education, mentoring, professional development.
• Team with excellent tech expertise; company-paid certifications.