As our Senior Director of Data, you will serve as the strategic visionary and executive engine powering our company’s data transformation. In this high-impact leadership role, you will redefine how we leverage information by driving enterprise data strategy, pioneering AI data readiness, commanding end-to-end pipeline engineering, and unlocking competitive advantages through cutting-edge predictive analytics. You will champion, build, and inspire a world-class team across data engineering, analytics, and data science, scaling modern infrastructure, deploying production-grade ML models, and relentlessly embedding a fearless, evidence-based, data-driven culture across every level of the organization.
Key Responsibilities1. Strategy & Organizational Data Leadership- Define and execute the enterprise data, AI data readiness, and analytics strategy aligned with business objectives.
- Champion a data-driven culture across departments by elevating data literacy and self-service analytics.
- Build, mentor, and lead high-performing teams of data engineers, data scientists, and analysts.
- Drive the AI data strategy, ensuring data is curated, labeled, and optimized for ML/AI model development and deployment.
- Oversee the end-to-end lifecycle of machine learning models, predictive analytics, and feature store infrastructure.
- Collaborate with business partners to identify high-impact AI/ML opportunities that drive strategic value.
- Oversee modern data engineering, architectural design, and reliable ETL/ELT pipelines for batch and real-time processing.
- Architect scalable data warehouses, data lakes, and modern data stack operations (MLOps).
- Establish governance policies to ensure high data quality, security, and global regulatory compliance (e.g., GDPR, CCPA).
- Deliver key executive dashboards, visualizations, and A/B testing frameworks to measure operational KPIs.
- Experience: 10+ years of progressive leadership experience across data engineering, analytics, and data science.
- Leadership: Proven track record of managing data engineering and ML teams while fostering a data-driven organizational culture.
- Technical Mastery: Strong hands-on knowledge of Python, SQL, modern ETL tools, cloud data warehouses, and major ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
- Architecture & Pipelines: Deep expertise in pipeline design, streaming data architectures, MLOps, and feature store management.
- Education: Master's or Ph.D. in Data Science, Computer Science, Statistics, or related quantitative field.
- Communication: Excellent capability to translate complex technical concepts into clear strategic insights for non-technical stakeholders.
The posted pay range represents the anticipated low and high end of the compensation for this position and is subject to change based on business need. To determine a successful candidate’s starting pay, we carefully consider a variety of factors, including primary work location, an evaluation of the candidate’s skills and experience, market demands, and internal parity.
For roles with on-target-earnings (OTE), the pay range includes both base salary and target incentive compensation. Target incentive compensation for some roles may include a ramping draw period. Compensation is higher for those who exceed targets. Candidates may receive more information from the recruiter.
Navan uses AI-assisted Automated Employment Decision Tool (Metaview) to assist with evaluating resumes against job qualifications for this role. All final decisions are made by human recruiters and hiring managers.
Human oversight: Metaview does not automatically reject candidates or make final hiring decisions. Our recruiters and hiring managers review all outputs and make the final hiring decision regarding every application.
Your rights: If you prefer to have your application reviewed without AI assistance, you may request a human evaluation by entering your email here. Your decision to do so will not affect how your candidacy is evaluated.
Please refer to our Candidate Privacy Notice for more information about our processing of personal data, and your rights.
Skills Required
- 10+ years of progressive leadership experience across data engineering, analytics, and data science
- Experience managing data engineering and machine learning teams
- Strong hands-on knowledge of Python and SQL
- Experience with modern ETL tools and cloud data warehouses
- Experience with major machine learning frameworks, such as PyTorch, TensorFlow, and scikit-learn
- Deep expertise in pipeline design and streaming data architectures
- Expertise in MLOps and feature store management
- Master's or Ph.D. in Data Science, Computer Science, Statistics, or a related quantitative field
- Excellent ability to translate complex technical concepts into strategic insights for non-technical stakeholders
What the Team is Saying
Navan Compensation & Benefits Highlights
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Healthcare Strength — Employer-sponsored medical, dental, and vision coverage extend to employees and dependents, alongside mental-health resources like Headspace. Employer-verified plan listings confirm active U.S. medical coverage.
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Leave & Time Off Breadth — Flexible vacation (unlimited PTO) is advertised in the U.S., while the U.K. page specifies five weeks of PTO, underscoring regional structure. A company-wide Quiet Week around year-end, paid holidays, and sick time are also referenced in benefits materials.
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Parental & Family Support — Paid parental leave is clearly defined at 16 weeks for the birthing parent and 10 weeks for the non-birthing parent. Family medical leave and related supports are also noted.
Navan Insights
What We Do
Navan (Nasdaq: NAVN) is the leading all-in-one business travel, payments, and expense management platform that makes travel easy for frequent travelers. From finding flights and hotels to automating expense reconciliation, with 24/7 support along the way, Navan delivers an intuitive experience travelers love and finance teams rely on. See how Navan customers benefit and learn more at navan.com.
Why Work With Us
At Navan, we’re never satisfied with the status quo, and we know breakthrough ideas come from diverse perspectives. We are committed to cultivating a workplace that reflects the diversity of the customers we serve while fostering leadership and innovation.
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Navan Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
In-person connections is the foundation of Navan, the connections forged through face-to-face interactions improve company culture and what we can achieve together. We operate on a hybrid working model, which we define as four days a week in-office.
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