Lead Data Infrastructure Engineer

Job Description Join us at Oracle Cloud Infrastructure (OCI), where we are redefining enterprise cloud solutions with a dynamic team of innovators dedicated to excellence. We combine the agility of a startup with the extensive reach of a leading enterprise software firm, empowering our teams to create groundbreaking solutions that deliver significant value to our customers. Our organization, OCI Horizon Data Platform & Analytics, is responsible for managing a fully self-service data platform utilized by 450 partner teams within OCI. We facilitate advanced analytics, machine learning, and generative AI-powered solutions that provide actionable insights and support impactful decision-making across various functions, including finance, operations, products, and support. We are looking for a Principal Engineer with a robust background in building and scaling data infrastructure, particularly for advanced analytics and AI/ML products. In this key role, you will lead the design, development, and deployment of next-generation analytics solutions, ensuring the security, scalability, and performance of our systems. This is an influential position where you will collaborate across teams, shape critical architectural decisions, optimize data pipelines, and spearhead innovative AI-driven analytics on the Oracle Cloud. Responsibilities: Lead the design, implementation, and optimization of scalable, high-performance data pipelines for large datasets, facilitating actionable insights and machine learning operations for partner teams in OCI. Establish data and operational governance throughout the entire data lifecycle, from ingestion to consumption. Create user-friendly interfaces on curated datasets to help customers extract insightful information from various sources. Contribute to the design of a next-generation scalable data platform and data lake focused on performance, availability, and data quality. Architect, design, and implement secure, scalable, and highly available infrastructure for cutting-edge analytics solutions on Oracle Cloud. Oversee proactive query optimization initiatives. Directly contribute to deploying complex analytics and ML pipelines, ensuring robust performance and minimal downtime across multi-region environments. Influence deliverables across multiple engineering teams by leading design reviews and contributing to development standards. Champion automation initiatives, developing advanced CI/CD pipelines and enforcing lifecycle policies to enhance development and operations. Uphold high standards for infrastructure security, compliance, and operational excellence at scale. Collaborate closely with engineering, data science, and business teams to translate strategic goals into innovative production-grade solutions while actively addressing operational challenges. Mentor fellow engineers while remaining actively engaged in coding, architecture reviews, and technical problem-solving. Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or a related field. 7+ years of hands-on experience in software or data engineering, including designing and operating large-scale data infrastructure. Strong programming skills in Java, Python, or Scala alongside SQL, with a proven record of delivering production-quality data solutions. Extensive knowledge of both relational and non-relational data stores, including SQL and performance tuning. Proven experience in building data governance frameworks for the complete data lifecycle. Hands-on experience in developing data pipelines and orchestration using tools like Apache Airflow. Experience implementing security best practices in software engineering. Ability to collaborate with product management to transform business requirements into technical specifications. Experience architecting cloud-based data infrastructure that is secure, scalable, and highly available. Familiarity with deploying CI/CD pipelines and automation tools like Terraform. Understanding of DevOps/ML Ops practices, with experience managing analytics or ML models in production being a plus. Ability to design and maintain RESTful APIs. Strong problem-solving skills to resolve complex technical challenges. Experience with containerization technologies. Preferred Qualifications: Master's degree or higher in Computer Science or a related field. 10+ years of experience in data infrastructure, cloud infrastructure, backend engineering, DevOps, or ML Ops roles. Experience optimizing large-scale analytics workloads. Experience in building production-grade MLOps workflows and deploying ML/AI models at scale. Familiarity with regulated environments and automated compliant infrastructure. Knowledge of building NLP to SQL GenAI assistants. Advanced coding skills in Python and Java, plus experience with distributed computing frameworks. Prior experience in supporting production systems or cloud operations. Deep understanding of cloud platform architectures (AWS, OCI, Azure) and best operational practices. Strong knowledge of data structures, algorithms, and software engineering principles. Experience in driving technical vision for AI-powered analytics solutions. Benefits: Comprehensive medical, dental, and vision insurance. Disability and life insurance. Flexible Spending Accounts for healthcare and dependent care. 401(k) with company match. Flexible vacation policies and paid time off. Paid holidays and sick leave. Paid parental leave and adoption assistance. Employee Stock Purchase Plan. Financial planning and legal support services. Voluntary benefits, including insurance options. This role requires compliance with applicable customer health mandates. Oracle is committed to equal employment opportunities for all qualified applicants without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or veteran status.

Created: 2026-03-04