Senior Data Engineer (Oracle FDI / Data Warehouse)

About Us
Tech9 is shaking up a 20-year-old industry, and we're not slowing down. Recognized by Inc. 5000 as one of the nation's fastest-growing companies, we are dedicated to building innovative, high-quality software and data solutions. Our team is passionate about craftsmanship, collaboration, and delivering technology that makes an impact. We offer a 100% remote working environment with a supportive culture that empowers you to do your best work.

Role Overview
We are seeking a Senior Data Engineer with deep expertise in Oracle and Fusion Data Intelligence (FDI) to support the Elevate Finance team as they enter the data warehouse build phase.

The project has completed discovery and requirements gathering—now it needs a highly technical, hands-on engineer to design and build scalable pipelines and warehouse components within Oracle’s ecosystem. You will partner closely with the existing data engineer and project leadership to translate business requirements into data models, reporting objects, and production-ready data flows.

This role requires someone who can operate independently, ramp quickly, and deliver high-quality engineering work within a fast-moving finance data environment.

Responsibilities

• Data Pipeline Development: Design, build, and maintain data pipelines and warehouse components within the Oracle ecosystem.
• Oracle FDI Expertise: Develop, support, and optimize reporting in Oracle Fusion Data Intelligence, including report creation when needed.
• Warehouse Build-Out: Enable the next phase of the Elevate Finance data warehouse, ensuring scalability, accuracy, and alignment with business needs.
• Collaboration & Requirements Translation: Work closely with the Elevate data engineer and project leadership to translate requirements into data models and deliverables.
• Best Practices: Contribute to standards for data quality, architecture, performance, and long-term maintainability.
• Problem Solving: Troubleshoot issues, optimize data flows, and ensure accuracy across financial datasets.
   

Minimum Qualifications

• Strong expertise with Oracle FDI (Fusion Data Intelligence) — core requirement.
• Experience developing or enabling reports in Oracle FDI — major plus and highly preferred.
• 3+ years working with Databricks. 
• 3+ years working in an Azure environment.
• Senior-level data engineering experience, with a proven ability to design and build pipelines, not just perform analysis or requirements gathering.
• Ability to operate independently, learn fast, and contribute meaningfully from day one.
• Strong communication and collaboration skills to work with cross-functional teams.
   

Preferred Qualifications

• Experience with data architecture, including conceptual, logical, or physical modeling.
• Background working in finance or ERP-related data environments.
• Familiarity with data quality frameworks or governance practices.
   

Why Join Us?

• High Impact: Play a key role in building a finance data warehouse from the ground up.
• Flexibility: 100% remote role based in LATAM with flexible hours.
• Collaboration: Work with a talented engineering team and directly influence architectural decisions.
• Growth: Deepen expertise in Oracle’s modern data ecosystem while contributing to a strategic enterprise initiative.
   

Interview Process

Our interview process is designed to move efficiently while ensuring transparency and alignment:

1. Introductory Call – 15 minutes -A brief conversation with our recruiting team to discuss your background, data engineering experience, and alignment with the role.

2. On-Demand HireVue Screening –15–30 minutes- Behavioral and situational questions focused on ownership, communication, data problem-solving, and ability to work independently.

3. Internal Technical Interview #1 – 1 hour- A deep technical discussion on Oracle FDI, Oracle-based data engineering, data modeling, and end-to-end pipeline design.

4. Internal Technical Interview #2 – 1 hour- Scenario-based evaluation focused on warehouse build-out, scalability, optimization, and navigating ambiguity in finance data environments.

5. Hiring Manager Interview – 30 minutes- A conversation about your experience, collaboration style, and ability to drive engineering work with limited oversight.

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