Senior Data Architect – FDI Pipeline Data Model Team

Oracle Analytics is used by customers across the world to discover deep insights about their business, improve collaboration around a single view by securely including all relevant data, and increase agility by quickly spotting patterns and powering data-driven decisions with AI and machine learning. 

Oracle Fusion Data Intelligence platform (FDI) is the next generation of Oracle Fusion Analytics Warehouse built for Oracle Fusion Cloud Applications, bringing together business data, ready-to-use analytics, and prebuilt AI and machine learning (ML) models to deliver deeper insights and accelerate the decision-making process into actionable results.

The backbone of FDI is the lights-out data pipeline that manages the data warehouse for all the customers. For details about the product, visit

https://docs.oracle.com/en/cloud/saas/analytics/25r3/index.html

 

FDI Pipeline Data Model team defines the application development language and uses the same to build applications – deliver analytic data models for Fusion, NetSuite, Salesforce etc. sources. 

As one of the senior technical leads on this team, you’ll define and drive the architectural vision for scalable, secure, and innovative data models and platforms supporting analytics and AI initiatives. You’ll lead the design and implementation of enterprise data solutions, set organization-wide standards, and collaborate with leaders across product, pipeline engineering, and content analytics teams. Your expertise will guide the integration of new technologies and influence data strategy at scale, ensuring industry-leading data quality, governance, and performance. In this role, you will mentor technical talent and help shape the future direction of FDI

 

You will

• Play a hands-on role in designing, developing, and optimizing scalable, secure data models and pipelines that power FDI analytics, machine learning, and AI-driven solutions.
• Serve as the primary subject matter expert and technical authority across multiple Fusion/NetSuite etc. modules, or entire pillars such as ERP, HCM, or SCM.
• Lead and influence key architectural decisions, setting technical direction, standards, and best practices for data modeling, automation, language processing, and user interface integration.
• Build strong relationships and partner with Pipeline engineering, product, and Content analytics leads to ensure alignment of technical solutions with business objectives, advocating for customer benefits.
• Full ownership and accountability for release features as Feature Owner, driving progress, coordinating across teams, and resolving roadblocks.
• Conduct thorough code and design reviews to ensure high performance, maintainability, and extensibility of team deliverables.
• Troubleshoot and resolve complex, high-impact data, pipeline, and platform issues, delivering robust and reliable end-to-end solutions.
• Drive innovation through adoption and hands-on implementation of new technologies, frameworks, and engineering approaches to continuously evolve FDI’s data platform capabilities.
• Mentor and coach engineers across the Pipeline and FDI teams on data management/modeling, building technical excellence and fostering a collaborative, innovation-driven culture.
• Actively participate in planning, technical design reviews, and cross-team forums, shaping the strategic data architecture for FDI

 

Qualifications:

You have: 

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, with 10+ years of hands-on experience architecting large-scale data solutions.
• Deep understanding of business processes and sources like Fusion.
• Advanced programming skills in Python, PySpark, Java, Scala and SQL, with proven success designing cloud-native data pipelines and platforms (Oracle Cloud, AWS, Azure, GCP).
• Strong command of data modeling, using leading tools and modern techniques (3NF, Dimensional, Data Vault, etc.) to create and maintain scalable enterprise data models.
• Hands-on experience with Spark, ETL/ELT frameworks, real-time streaming (Kafka/EventHub), and automation across diverse data environments.
• Practical background in AI, LLMs, or machine learning-enabled development—and an eagerness to innovate and learn as the tech evolves.
• Natural collaborator and mentor, comfortable guiding both technical teams and business partners, and able to communicate complex ideas with clarity and impact.