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

1. 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.

2. 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.

3. 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).

4. 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.