Veeva Systems is a mission-driven organization and pioneer in industry cloud, helping life sciences companies bring therapies to patients faster. As one of the fastest-growing SaaS companies in history, we surpassed $3B in revenue in our last fiscal year with extensive growth potential ahead.
At the heart of Veeva are our values: Do the Right Thing, Customer Success, Employee Success, and Speed. We're not just any public company – we made history in 2021 by becoming a
public benefit corporation (PBC), legally bound to balancing the interests of customers, employees, society, and investors.
As a
Work Anywhere company, we support your flexibility to work from home or in the office, so you can thrive in your ideal environment.
The Role
A Senior Data Engineer who can lead the design and implementation of our next-generation Data Lakehouse. In this role, you will be designing and implementing our unified storage and compute layer, bridging the gap between the flexibility of a data lake and the performance of a traditional warehouse. You will be responsible for designing data ingestion for a large volume of data, and optimizing the storage for performant downstream analytics.
What You’ll Do
Design and implement a scalable Lakehouse environment. Own the lifecycle of efficient storage, including schema evolution, partition transformation, and snapshot management.
Build and manage real-time and batch data ingestion pipelines using Kafka and Spark
Deploy, manage, and scale data workloads (such as Spark executors) using Kubernetes (EKS).
Develop complex ETL workflows. Optimize jobs for large-scale data processing focusing on memory management and shuffle optimization.
Manage and monitor end-to-end data lifecycles using orchestration tools
Write and tune high-performance queries against the Lakehouse. Implement optimization strategies, compaction, and data skipping to reduce latency and cloud costs
Requirements
5+ years in Data Engineering, with at least 2 years focused on Lakehouse or modern Data Lake environments
Hands-on experience with AWS ecosystems, async/queue processing in a production environment and working with a Lakehouse
Expert in workflow management, data transformation, storage and exchange at scale.
Proven experience with events driven job processing. Mastery in data ingestion, processing large-scale data and performance tuning.
Experience with Kubernetes and infrastructure as code
Nice to Have
Experience with query engines like Starrocks or Druid
Familiarity with building and monitoring dashboards on K8s-based data clusters
Perks & Benefits
Medical, dental, vision, and basic life insurance
PTO and company-paid holidays
Retirement programs
1% charitable giving program
Compensation
Base pay: $115,000 - $175,000
The salary range listed here has been provided to comply with local regulations and represents a potential base salary range for this role. Please note that actual salaries may vary within the range above or below, depending on experience and location. We look at compensation for each individual and base our offer on your unique qualifications, experience, and expected contributions. This position may also be eligible for other types of compensation in addition to base salary, such as variable bonus and/or stock bonus.
#LI-Remote
Veeva’s headquarters is located in the San Francisco Bay Area with offices in more than 15 countries around the world.
Veeva is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity or expression, religion, national origin or ancestry, age, disability, marital status, pregnancy, protected veteran status, protected genetic information, political affiliation, or any other characteristics protected by local laws, regulations, or ordinances. If you need assistance or accommodation due to a disability or special need when applying for a role or in our recruitment process, please contact us at
talent_accommodations@veeva.com.
