The Role
Build and maintain NitroAI's data engineering infrastructure: own and scale the Airflow codebase, design and productionize pipelines, onboard new data sources, operate large-scale Spark pipelines on AWS Glue and support migration to Databricks, improve commercial pharma data models and lineage, and maintain internal Python packages while mentoring analytics teams.
Summary Generated by Built In
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.
Join us in transforming the life sciences industry, committed to making a positive impact on its customers, employees, and communities.
The NitroAI team is seeking a Senior Data Engineer to build and maintain the data engineering infrastructure that powers our analytics delivery. You'll work alongside data scientists and analytics teams to productionize manual solutions, build governed datapipelines, and deliver data to customers at scale. This is a high-impact, high-ownership role in a startup-like environment within Veeva — with immediate influence over how NitroAI delivers data across a growing multi-tenant platform.
What You'll Do
- Own the Airflow codebase end-to-end (MWAA, ~100 DAGs currently): build reusable templates, scale patterns, enforce standards, improve testing infrastructure
- Serve as delivery teams’ go-to on pipeline architecture and troubleshooting
- Own data onboarding when we connect to a new source including connection setup, schema discovery, initial pipeline design
- Operate and extend large-scale Spark pipelines on AWS Glue, including multi-TB joins and compaction jobs, and support migration of those workloads to Databricks as we move platforms
- Drive data model improvements around our commercial pharma data (patient claims, KOL and HCP data, CRM activity) with a focus on structure, lineage, and how it flows through the platform
- Contribute to and maintain our internal Python package used across the data team
Requirements
- 5+ years building data models and pipelines
- 2+ years production Airflow experience
- 2+ years Spark at scale: hands-on experience with multi-TB datasets; AWS Glue experience preferred
- Strong python and SQL
- AWS fluency in S3, ECS/Fargate, Glue, IAM, Secrets Manager
- Clear communicator who can teach: onboarding analytics team to the codebase and developing team Airflow capability is a core part of this job, not a side responsibility
Nice to Have
- Experience working with privacy-sensitive or governed data
- Databricks experience – we’re actively migrating Glue workloads there
- Proficiency with Claude Code
- Exposure to data science workflows and ML pipeline tooling
- Background in life sciences or healthcare
- Experience with Open Meta data or similar data catalog and data dictionary tooling
Interviewing with Veeva
- Follow the application process and submit your resume.
- Within 3 days, you will receive a link to a personality assessment administered by a third party.
- Once you complete the assessment, our team will review your full application package and follow up via email with our decision.
- If moving to the interview stage, the process is as follows:
- A conversation with the hiring manager
- A practical case exercise
- A final conversation with our group's Senior Leader.
- Once all interviews are complete, the manager will be in touch with a final decision.
We value your time and believe in a transparent hiring process. Here is the process you can expect.
Perks & Benefits
- Medical, dental, vision, and basic life insurance
- Flexible 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-RemoteUS#LI-MidSenior
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 [email protected].
Skills Required
- 5+ years building data models and pipelines
- 2+ years production Airflow experience
- 2+ years Spark at scale (hands-on with multi-TB datasets)
- Strong Python
- Strong SQL
- AWS fluency: S3, ECS/Fargate, Glue, IAM, Secrets Manager
- Clear communicator who can teach and onboard analytics teams
- Experience working with privacy-sensitive or governed data
- Databricks experience
- Proficiency with Claude Code
- Exposure to data science workflows and ML pipeline tooling
- Background in life sciences or healthcare
- Experience with Open Meta data or similar data catalog and data dictionary tooling
Veeva Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Veeva and has not been reviewed or approved by Veeva.
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Equity Value & Accessibility — Equity is broadly distributed across the company, positioning most employees as shareholders. Stock-based incentives can materially enhance total compensation, particularly at higher seniority.
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Flexible Benefits — Work Anywhere enables remote-first flexibility with options to use offices and to gather through offsites or coworking weeks. This structure supports collaboration while minimizing rigid on-site requirements.
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Healthcare Strength — Core coverage includes medical, dental, vision, HSA/FSA, life and disability, and EAP. Supplemental perks such as commuter assistance and wellness or gym reimbursements are available in some locations.
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The Company
What We Do
Veeva is the global leader in cloud software for the life sciences industry. Committed to innovation, product excellence, and customer success, Veeva serves more than 1,000 customers, ranging from the world’s largest pharmaceutical companies to emerging biotechs. As a Public Benefit Corporation, Veeva is committed to balancing the interests of all stakeholders, including customers, employees, shareholders, and the industries it serves.
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