Senior Principal Member of Technical Staff

At Oracle Cloud Infrastructure (OCI), we are shaping the future of enterprise cloud with a diverse team of innovators committed to excellence. Blending the agility of a start-up with the global reach of the world's leading enterprise software company, we empower our teams to create breakthrough solutions and deliver value to our customers. Our org (OCI Horizon Data Platform & Analytics) manages the fully self-service based data platform for 450 partner teams in OCI. We enable and build advanced analytics, machine learning, and generative AI-powered solutions and applications that provide actionable insights and drive impactful decision making across OCI, including finance, products, operations, support, and more.

We are seeking a Senior Principal Engineer with deep expertise in building and scaling data infrastructure to enable advanced analytics and AI/ML products for Horizons partner teams and OCI executives. In this role, you will also lead the design, development, and deployment of next-generation AI-driven analytics solutions. You will ensure the security, scalability, and performance of our systems, driving forward OCI's mission to deliver intelligent cloud experiences. This is a highly impactful role where you will collaborate cross-functionally, shape critical backend and Data architecture decisions, optimize data pipelines, build governance, and drive innovation in AI-powered analytics on the Oracle Cloud. If you thrive on big challenges and want to help define the future of cloud intelligence, we would love to meet you.

In this role, you will:

· Influence multiple teams to design, implement and optimize large-scale data pipelines and underlying infrastructure for batch and real time processing using SQL and Big Data processing engines where needed, on top of large Relational and Non-Relational data stores striking right balance between consistency, availability, scale, and performance.

· Build and onboard the best-in-class data quality, platform observability and data governance framework for the platform and key analytics workflows.

· Be a leading contributor in the next phase of the Horizon data platform architecture that runs on 5X the current state, to provide delightful customer experiences related to usage, performance, scale, observability, and reliability.

· Design and implement comprehensive automation pipelines for infrastructure, security, and compliance, enabling seamless policy enforcement throughout the product lifecycle.

· Help build the backend infrastructure that enables the best-in-class GenAI/ML products on the cloud.

Basic Qualifications

· Bachelor's degree in computer science, Engineering, or a related or related quantitative field.

· 10+ years of hands-on software or data engineering experience, including direct responsibility for designing, building, and operating well governed large-scale data infrastructure, data platform and data lake.

· Extensive programming and coding expertise in Java/Python/Scala plus SQL, with a proven track record of delivering production-quality data solutions.

· Excellent knowledge and experience in RDBMS and Non-Relational data stores. Demonstrated experience in SQL. Deep Query performance tuning experience and knowledge is highly desirable but not mandatory.

· Solid experience in building and enabling data and operational governance for the full lifecycle of the data journey from ingestion to consumption.

· Hands-on experience in extensible data pipeline development and orchestration with tools like Apache Airflow, Step Functions, etc.

· Experience architecting, implementing, and operating secure, scalable, and highly available cloud-based data infrastructure.

· Solid experience in implementing software engineering security best practices and contributing to design/engineering for SecOps.

· Practical experience deploying and optimizing CI/CD pipelines, automation tools, and infrastructure as code (e.g., Terraform, Ansible).

· Proven experience influencing and partnering with product management, TPMs in translating business requirements into data and engineering specifications.

· Solid understanding of DevOps/ML Ops practices. Desirable to have some hands-on experience in building, deploying, and managing analytics/ML models in production.

· Proven ability to design, evolve, and maintain RESTful APIs (OpenAPI/Swagger).

· Proven ability to drill into code, resolve complex technical challenges, and actively contribute to problem resolution in high-impact projects.

· Effective communication and collaboration skills, with the ability to mentor others while remaining involved in implementation deliverables.

· Experience and knowledge in containerization technologies.

Preferred Qualifications

· Master's or higher degree in Computer Science or a related field.

· 12+ years of professional experience in data infrastructure, cloud infrastructure, backend engineering, DevOps, or ML Ops roles.

· Recognized certifications in Data platforms, cloud computing, security, or DevOps methodology.

· Demonstrated experience operating and optimizing large-scale analytics workloads (Spark, Autonomous Data Warehouse, Object Storage).

· Experience in building production-grade MLOps workflows and deploying ML/AI models at scale highly desirable.

· Experience designing secure, automated, and compliant infrastructure in regulated environments.

· Experience building or enabling NL to SQL GenAI assistants and agents.

· Advanced coding skills in Python and Java, plus experience with distributed computing frameworks (Spark, Flink) and building lakes on non-relational stores.

· Prior roles supporting major production systems, operations, cloud support, or similar high-availability domains.

· Strong knowledge of cloud platform (AWS, OCI, Azure) architectures and operational best practices.

· Deep understanding of data structures, algorithms, and software engineering best practices.

· Experience in progressive rollout strategies and driving the technical vision for AI-powered analytics solutions.