Overview As a key member of the team, you will be responsible for designing, building, and maintaining the data pipelines and platforms that support analytics, machine learning, and business intelligence. You will lead a team of data engineers and collaborate closely with cross-functional stakeholders to ensure that data is accessible, reliable, secure, and optimized for AI-driven applications Responsibilities Architect and implement scalable data solutions to support LLM training, fine-tuning, and inference workflows. Lead the development of ETL/ELT pipelines for structured and unstructured data across diverse sources. Ensure data quality, governance, and compliance with industry standards and regulations. Collaborate with Data Scientists, MLOps, and product teams to align data infrastructure with GenAI product goals. Mentor and guide a team of data engineers, promoting best practices in data engineering and DevOps. Optimize data workflows for performance, cost-efficiency, and scalability in cloud environments. Drive innovation by evaluating and integrating modern data tools and platforms (e.g., Databricks, Azure etc) Qualifications Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field. 7+ years of experience in data engineering, with at least 2+ years in a leadership or senior role. Proven experience designing and managing data platforms and pipelines in cloud environments (Azure, AWS, or GCP). Experience supporting AI/ML workloads, especially involving Large Language Models (LLMs) Strong proficiency in SQL and Python Hands-on experience with data orchestration tools