Senior Data Engineer - Clinical Trials (Pharma)

Sintesys North America - Servicenow And Nearshore Specialists; Teletrabalho; BRL 80.000 - 120.000; Tempo integral

Resumo da oferta

A leading nearshore technology provider is hiring a Senior Data Engineer for Clinical Trials. The ideal candidate will possess hands-on experience with clinical trial data, CTMS, EDC, and eTMF systems. Responsibilities include designing data pipelines and supporting analytics in regulated environments. Candidates must have at least 5 years of data engineering experience and strong AWS skills. The position offers a remote work option within LATAM.

Qualificações

• 5+ years of experience as a Data Engineer.
• Mandatory experience in pharma/clinical trials.
• Hands-on with CTMS, EDC, and eTMF.

Responsabilidades

• Design and maintain data pipelines for clinical trial data.
• Integrate data from CTMS, EDC, and eTMF systems.
• Support analytics and reporting in regulated (GxP) environments.

Conhecimentos

Data Engineering

AWS (Glue, Airflow, Athena, EMR)

SQL

Python

Databricks/Spark

Ferramentas

CTMS

EDC

eTMF

Descrição da oferta de emprego

🚨 We’re Hiring | Senior Data Engineer – Clinical Trials (Pharma) 🚨

🌎 Remote | Nearshore | LATAM

We’re looking for a Senior Data Engineer with hands‑on experience in clinical trials and pharmaceutical data environments to support ongoing and upcoming projects.

This is a domain‑specific role — strong cloud skills are required, but clinical trial experience is mandatory.

🔬 What You’ll Work On

• Designing and maintaining data pipelines for clinical trial data
• Integrating data from CTMS, EDC, and eTMF systems
• Supporting analytics and reporting in regulated (GxP) environments
• Collaborating with clinical operations, biostatistics, and IT teams

🧠 Required Experience

• ✅ 5+ years as a Data Engineer
• ✅ Experience in pharma / clinical trials (this is a must)
• ✅ Hands‑on with CTMS, EDC, eTMF
• ✅ Strong AWS experience (Glue, Airflow, Athena, EMR)
• ✅ Databricks / Spark , SQL, Python
• ✅ Familiarity with CDISC / SDTM and regulated data standards