Principal Data Engineer

Location: Nashville, TN, United States

Provides expertise on the design and participates in building of data infrastructure to optimize data processing from a variety of data sources. Independently designs and implements data governance policies and procedures for data handling to manage data consistency, integrity, accuracy, and reliability. Provides expertise on and participates in the design and implementation of rigorous data validation and integrity checks, proactively mitigating data quality issues that could impact data pipeline and model performance. Leverages advanced knowledge of Extract, Transform, and Load (ETL) processes to design, develop, and optimize automated, scalable, and efficient data pipeline architectures to build reusable data products. Works independently and collaboratively in an agile development environment with other engineers to develop, maintain, and debug advanced data solutions that are scalable, efficient, cost effective, and reliable.

About Us

Only Oracle brings together the data, infrastructure, applications, and expertise to power everything from industry innovations to life-saving care. And with AI embedded across our products and services, we help customers turn that promise into a better future for all. Discover your potential at a company leading the way in AI and cloud solutions that impact billions of lives.

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As a Principal Data Engineer, you will be at the forefront of Oracle’s Cloud Infrastructure Marketplace data initiatives, playing a pivotal role in transforming raw data into actionable insights. Collaborating with OCI engineering leadership, product managers, data scientists and business stakeholders, you will design scalable data pipelines, optimize data infrastructure, and ensure the availability of high-quality datasets for strategic analysis. This role goes beyond data engineering, requiring hands-on involvement in statistical analysis and predictive modeling. You will use techniques such as regression analysis, trend forecasting, and time-series modeling to extract meaningful insights from data, directly supporting business decision-making.