Head of Data & AI Engineering

Are you an experienced data and AI leader passionate about building and running enterprise-scale data platforms in a fast-paced technology environment? Our client is seeking a Head of Data & AI Engineering to lead the design, development, and operational management of cutting-edge data and AI solutions that power the business.About the Role:As Head of Data & AI Engineering, you will combine strategic leadership with hands-on technical execution to build scalable, high-performance data platforms, implement AI/ML solutions, and ensure operational excellence. You will work closely with engineering, product, and analytics teams to deliver actionable insights while maintaining a robust, secure, and scalable data infrastructure.Key Responsibilities:Lead the design, build, and operation of modern data and AI platforms, including data lakes, warehouses, streaming pipelines, and ML infrastructure.Develop and implement end-to-end data pipelines (ETL/ELT) to support analytics, AI/ML, and operational applications.Operationalize AI/ML models, ensuring reliability, scalability, and performance in production.Ensure data quality, governance, security, and compliance across platforms and pipelines.Partner with cross-functional technology teams to define architecture, standards, and best practices for data and AI engineering.Build, mentor, and lead a high-performing team of data engineers, ML engineers, and architects, fostering a culture of innovation and technical excellence.Evaluate and implement emerging technologies to improve data platform capabilities, AI pipelines, and operational efficiency.Collaborate with cloud, DevOps, and software engineering teams to optimize cloud-native infrastructure (AWS, Azure, GCP).Requirements:Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI/ML, or related technical field.10+ years of experience in data engineering, AI/ML engineering, or platform engineering, with at least 3–5 years in a leadership role.Hands-on experience designing and running enterprise-scale data platforms, real-time data pipelines, and production AI/ML systems.Expertise in Python, Java, Scala, Spark, Kafka, or other modern data engineering/streaming frameworks.Deep experience with cloud platforms (AWS, Azure, GCP), containerization (Docker, Kubernetes), and MLOps frameworks.Strong understanding of data modeling, data architecture, and distributed systems.Proven ability to manage technical teams, vendor relationships, and large-scale projects in a technology-driven environment.Strong communication and stakeholder management skills. EA Licence No: 11C5502 | EAP Registration No: R1106192