Description:

Veeva Systems is a mission-driven organization and pioneer in industry cloud, helping life sciences companies bring therapies to patients faster.
The company has surpassed $2B in revenue in its last fiscal year and has extensive growth potential ahead.
Veeva is a public benefit corporation (PBC), legally bound to balance the interests of customers, employees, society, and investors.
The role involves working on Veeva Link, which supports the life sciences industry by connecting professionals with key people for clinical trials, education programs, and advisory boards.
As a data engineer, you will focus on data pipelines and take responsibility for a major part of the Link data processing platform.
You will find, design, and implement improvements to the product's data pipelines and adjust them to changing market demands.
Responsibilities include working on Veeva Link’s next-gen Data Platform, improving the current environment, and operating ML models in cooperation with the data science team.
You will work with JVM-based languages or Python on Spark-based data pipelines and experiment to improve precision, recall, or cost savings.

Requirements:

Expert skills in Java or Python are required.
Experience with Apache Spark or PySpark is necessary.
You must have experience writing software for the cloud, specifically AWS or GCP.
Proficiency in speaking and writing in English is essential for day-to-day conversations and technical discussions.
Nice to have: Experience with operating machine learning models (e.g., MLFlow).
Nice to have: Experience with Data Lakes, Lakehouses, and Warehouses (e.g., DeltaLake, Redshift).
Nice to have: DevOps skills, including terraform and general CI/CD experience.
Nice to have: Previous experience working in agile environments.
Nice to have: Experience with expert systems.

A comprehensive benefits package is offered.
Annual allocations for continuous learning, development, and charitable contributions are provided.
Fitness reimbursement is included.
Veeva supports a Work-Anywhere policy, allowing flexibility to work from home or in the office.