Geared toward senior data leaders comfortable with AI strategy and pipeline architecture, this role demands a strong background in data science and analytics, with a focus on enterprise-level infrastructure and cross-functional collaboration in San Francisco.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Navan
Position Overview
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 Responsibilities
- 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.
- AI Readiness & Data Science Leadership
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.
- Pipeline Engineering & Infrastructure
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).
- Governance, Analytics & Reporting
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.
Qualifications
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.
Pay Range$194,400—$432,000 USD
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Source: Navan careers