Lead Data Engineer

3 days ago

Singapore KUOK (SINGAPORE) LIMITED Full time

Job Summary We are seeking a highly skilled and motivated Lead Data Engineer to oversee the design, development, and deployment of enterprise-grade data pipelines and analytics platforms. This individual will lead a team of Data Engineers, ensuring best practices in design, performance, scalability, and governance. In addition to driving current Data Engineering efforts, the role will play a pivotal part in expanding the team's scope towards next-generation AI technologies, where data serves as the foundation for innovation. Responsibilities Team leadership and Oversight Supervise and mentor a team of Data Engineers, setting clear goals, KPIs, and development plans. Review, approve, and provide feedback on data pipeline and data model designs. Foster a culture of continuous improvement, innovation, and accountability. Data Engineering Excellence Lead the development, optimization, and deployment of reliable data pipelines to Production. Ensure adherence to best practices in architecture, coding standards, security, and compliance. Troubleshoot and resolve complex data pipeline and integration issues Innovation & AI Expansion Explore and integrate emerging technologies such as Retrieval-Augmented Generation (RAG), text‐to‐SQL, and other AI‐driven data solutions. Work closely with the Data/AI Lead to identify opportunities where data can fuel advanced AI applications and business insights. Stay updated with the latest industry trends in Data, Cloud, and AI Collaboration & Governance Partner with stakeholders across business and IT to align solutions with organizational objectives. Ensure compliance with data governance, lineage, and quality frameworks. Collaborate with DevOps and Data Governance teams for smooth deployment and lifecycle management Requirements Education Bachelor in Computer Science or its equivalent Experience 5+ years in Data Engineering (or adjacent roles) delivering production‐grade data solutions; 2+ years as a tech lead or people lead. Proven track record reviewing and approving data architecture/designs and promoting to Production in governed environments Technical Expertise Strong experience in ETL/ELT pipeline development, cloud‐based data platforms (Azure, AWS, or GCP), and data modeling. Proficiency in SQL, Python, Spark, Synapse/Fabric, Databricks, or equivalent. Knowledge of MLOps, containerization (Docker, Kubernetes) is an advantage. Exposure to AI technologies such as LLMs, RAG, and text‐to‐SQL preferred Leadership & Growth Mindset Proven ability to lead, mentor, and inspire technical teams. Strong problem‐solving, critical thinking, and decision‐making abilities. Open to learning, adaptable to new technologies, and proactive in applying innovative solution Certification (Preferred but not mandatory)Microsoft Certified: Azure Data Engineer Associate / Azure Solutions Architect Google Cloud Professional Data Engineer / AWS Certified Data Analytics – Specialty Databricks Certified Data Engineer Associate / Professional Certifications in AI/ML or MLOps (e.g., TensorFlow, OpenAI, AWS ML, Azure AI Engineer) are a plus #J-18808-Ljbffr

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