TL;DR

Middle Data Engineer (Databricks, PySpark): Building and maintaining data pipelines for clinical data surveillance and analytics initiatives with an accent on GxP-compliant data processes and integration with enterprise platforms. Focus on developing robust ETL/ELT solutions, managing data security, and creating unified datasets for reporting.

Location: Onsite in Ukraine

Company

%hirify_global% is a global technology company with over 6000 specialists, providing a full spectrum of services including business and tech advisory, enterprise solutions, and software development.

What you will do

Develop and maintain data pipelines using Databricks and PySpark.
Support clinical data surveillance workflows.
Assist in implementing GxP-compliant data handling and documentation.
Manage role-based access control for sensitive datasets.
Contribute to Databricks integration with Azure and SNAP platforms.
Match, merge, and standardize data from various sources to build unified datasets.

Requirements

Hands-on experience with Databricks and Python (PySpark).
Understanding of clinical or regulated data environments (GxP as a plus).
Basic to intermediate experience with data security concepts (RBAC, access control, permissions).
Experience working with ETL/ELT pipelines and data engineering best practices.
Good communication skills and ability to collaborate with stakeholders.
Must be located in Ukraine.

Culture & Benefits

Equal opportunities in recruitment and career development.
Commitment to fostering a diverse work environment where everyone feels free to be themselves.
Support for employees, candidates, and business partners.
Focus on personal and professional growth.

Hiring process

Application review.
Talent Acquisition Interview.
Technical Interview.
Customer Interview (for some roles).
Job Offer.