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Full Stack Engineer role at Veeva Systems, contributing to a data intelligence product for the Life Sciences industry. Responsibilities include developing and maintaining a web platform, integrating front and back-end components, and collaborating with product and data teams for new features and optimizations.

Veeva Systems is looking for a DevOps Engineer with experience in software development and DevOps to design, implement, and maintain cloud infrastructure supporting data-intensive applications. The role involves architecting and improving infrastructure, ensuring scalability and reliability, and supporting development teams.

As an Engagement Manager at Veeva Systems, you will lead consulting projects in the research and development (R&D) space, managing teams and driving business development initiatives. You will be responsible for end-to-end project delivery, building strong client relationships, and developing thought leadership in the life sciences industry.

Veeva Systems is seeking a DevOps Engineer with 4+ years of experience in software development and at least two years of DevOps experience. The role involves designing, implementing, and maintaining cloud infrastructure, ensuring scalability and reliability, and supporting development teams with infrastructure needs.

Join Veeva Systems as a DevOps Engineer to design, implement, and maintain cloud infrastructure supporting data-intensive applications. Collaborate with teams to improve platform scalability, availability, and reliability. Requirements include 4+ years of software development experience with 2 years in DevOps, hands-on experience with modern programming languages, security practices, and containerized applications.

As a Data Platform Engineer at Veeva Link, you will focus on the Data Platform and be responsible for features, innovation, and system landscape. You will work with JVM-based languages, preferably Python or Java, on Spark-based data pipelines.

Data Platform Engineer role at Veeva Link focusing on Data Platform, working on next-gen Data Platform, improving current environment with features and refactoring, using JVM-based languages on Spark-based data pipelines, and applying software engineering skills to build maintainable data applications.