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 technical leads on this team, you will design and deliver robust, scalable data architectures and models to power advanced analytics and AI-driven insights. You’ll partner with cross-functional teams to integrate diverse data sources and set best practices for data quality, performance, and security. Your leadership will help drive the adoption of innovative tools and design patterns, while mentoring junior engineers and guiding team standards. You will play a key role in shaping the data platform that supports FDI’s next generation of solutions.

You will: 

• Collaborate with product managers and engineers to translate business and functional requirements into effective, analytical data models.
• Serve as the primary subject matter expert and technical authority across multiple Fusion/NetSuite etc. modules.
• Design, build, and optimize scalable data models and pipelines to support reporting, analytics, and machine learning solutions, ensuring clarity and performance.
• Lead and participate in software engineering projects involving automation, language processing, and user interface development within Data Pipeline team.
• Full ownership and accountability for release features as Feature Owner, driving progress, coordinating across teams, and resolving roadblocks.
• Conduct code reviews and champion best practices for data engineering, focusing on explainability, maintainability, and extensibility.
• Ensure deliverable quality by working with QA to validate data correctness, consistency, and backward compatibility.
• Troubleshoot and resolve data issues, including mismatches and performance bottlenecks, for reliable data solutions.
• Monitor deployment metrics and customer feedback to identify and drive enhancements in existing systems.
• Stay current with emerging technologies and industry trends, evaluating new tools and approaches for adoption.
• Participate in team planning, backlog grooming, and technical design reviews.
• Mentor junior engineers and contribute to a collaborative, innovative, and continuously improving team environment

Qualifications:

You have:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, with 6+ years of hands-on experience designing, building, and optimizing data models and pipelines.
• Deep expertise in cloud databases, data modeling, and ETL processes, as well as experience working with at least one public cloud platform (Oracle Cloud, AWS, Azure, or Google Cloud).
• Strong programming skills in Python, PySpark, Java, Scala or SQL, and are comfortable working with distributed data systems.
• A solid grasp of data management, software design fundamentals, and best practices for building scalable and reliable analytics solutions.
• Recognition as a go-to expert for specific Fusion or NetSuite modules, or deep domain knowledge in areas such as ERP or HCM.
• Valuable practical experience in data pipeline orchestration, automation, or language processing.
• Excellent communication and collaboration skills—adept at partnering with engineers, product teams, and QA, as well as mentoring junior colleagues.
• A constant eagerness to learn, innovate, and contribute new ideas within a supportive, agile, and inclusive team environment

 

Disclaimer:

Certain US customer or client-fac