Data Engineer

Team

The Fusion Applications as a Service team is building a next generation cloud platform that supports the most demanding mission-critical customer requirements, operating at global scale to provide a secure, distributed, multi-tenant cloud environments for Fusion and other Oracle applications. This is your opportunity to be a core part of the team that defines and delivers exciting new capabilities for Oracle’s flagship Fusion Applications Cloud Services space. We are seeking a candidate with strong software development and/or system engineering experience in platform level products or services.

The ideal candidate possesses requisite data engineering and technical competencies coupled with exceptional curiosity and creativity. While the core responsibilities revolve around enhancing our ETL processes and SQL expertise, proficiency in Python and hands-on experience with Cloud platforms (ex. OCI)  are strongly preferred. In addition to technical proficiency, effective communication of complex data trends to organizational leaders is imperative. We seek an individual who is not only adept in technical aspects but also demonstrates strong interpersonal and communication skills.

Career Level – IC2

Responsibilities for this role:

• Address business challenges around Reliability Engineering, Performance Analytics, Capacity Forecasting and  deliver key insights and intelligence directly to the consumers across the DevOps team, executives across the entire leadership spectrum.
• Create, maintain data pipelines using ELT and ETL processes to build reusable data products.
• Collaborate closely with data science, ML  and BI teams to develop robust data models and pipelines for advanced analytics and machine learning applications.
• Advocate for best practices and foster a culture of continuous learning within the team. 

Skills

• 3 yrs or more experience in data engineering with large datasets across disparate data sources (API, relational databases, object store) and curating them  for data science /AI/ML implementations
• Proficiency in creating and maintaining optimal, scalable data pipelines for analytics and model training using cloud native tooling for  data pipelines (Azure Data Factory, AWS Glue or similar)
• Expertise in ETL, cataloging, curating and analyzing large, complex and disparate data sets
• Proficiency using data scripting tools (python, Scala, R) and ETL orchestration tools (Apache Airflow) is a plus
• Good understanding of Cloud Native technologies around

Interested candidates are encouraged to submit their resumes along with relevant work samples. We eagerly anticipate reviewing your application.

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