Senior Director, Data

As our Senior Director of Data you will serve as the strategic visionary and executive engine powering our companys data 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.

• • 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: Masters 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.