Director, Data Engineering - ML / AI

About the Role

Calling all data engineering leaders!

Are you passionate about cutting-edge Machine Learning and its potential to revolutionize data products? Do you thrive in a fast-paced, collaborative environment? If so, our team wants you!

Your Mission :

Own the Charge : Lead our Data Platform Team, driving innovation in data ingestion and management within our secure machine learning development environments.

Build and Optimize : Design and oversee large-scale data ingestion pipelines, ensuring data integrity and security.

Collaborate : Partner with product teams, data scientists, and engineers to drive innovation and deliver outstanding results.

Mentor and Encourage : Foster a culture of technical excellence, empowering your teams to reach new heights.

Why Workday?

Work-Life Balance : We believe in a healthy balance between work and personal life.

Financial Stability : Join a market leader recognized for its stability and growth.

Best Company Culture : Experience an encouraging and collaborative environment where innovation thrives.

About You

Basic Qualifications

Proven experience (10+ years) in data engineering, data management, or a similar role with 5+ years leadership experience in managing large teams (15+) a mix of managers, data engineers, software development engineers and more

Deep technical experience; architecture-level strength in designing data platforms that meet business objectives in collaboration with a strong technical team

Strong understanding of data governance principles, data quality management, data lifecycle, security, and compliance

Experience building pipelines using large-scale data technologies such as Kafka and Spark on cloud platforms

Other Qualifications

Experience in a machine learning or AI-driven organization.

Knowledge of AI / ML technologies such as GenAI , information retrieval (IR), recommender systems, query understanding and intent AI, LLMs, relevance AI, image and language understanding

Expertise in managing streaming data pipelines at scale

Experience in of MLOps / DevOps / CloudOps