Oracle Cloud Infrastructure (OCI) is seeking a Senior Data Engineer to join the Capacity Data Analytics team. This team develops the trusted data foundation, reporting platforms, self-service analytics solutions, and data management infrastructure that enable strategic decision-making across OCI's Compute, Storage, Networking, and Data Center organizations.
In this role, you will partner closely with engineering, business, finance, and operations stakeholders to design and deliver scalable data solutions that transform complex operational data into trusted, actionable insights. You will work on ambiguous, high-impact problems while helping define and maintain the canonical datasets used to measure operational efficiency and inform long-term infrastructure planning.
The ideal candidate is passionate about data engineering, possesses exceptional SQL expertise, enjoys solving challenging analytical problems, and thrives in a highly collaborative environment.
Why Oracle Cloud Infrastructure?
OCI is one of the world's fastest-growing cloud platforms, powering mission-critical workloads for enterprises around the globe. The Capacity Data Analytics team plays a strategic role in enabling OCI's continued growth by delivering trusted data, scalable analytics platforms, and self-service capabilities that support infrastructure planning and operational excellence.
Our team values collaboration, ownership, curiosity, and continuous learning. We embrace challenging problems, move quickly, and continually improve our data platforms to support a rapidly evolving cloud business.
Internal Responsibilities
Responsibilities
Design, develop, test, validate, document, and maintain scalable data engineering solutions and self-service analytics platforms.
Build high-quality SQL-based data pipelines, curated datasets, and reusable data models that support reporting and analytical workloads.
Develop and maintain canonical datasets that serve as trusted sources for strategic and operational decision-making.
Partner with engineering, finance, product, and business stakeholders to understand requirements and translate complex business problems into scalable data solutions.
Own projects from requirements through production delivery, ensuring accuracy, maintainability, and operational excellence.
Clearly communicate data lineage, assumptions, business rules, and transformation logic to both technical and non-technical audiences.
Continuously improve data quality, governance, documentation, and engineering best practices.
Support the development of self-service reporting capabilities that empower stakeholders across OCI.
Identify opportunities to automate manual processes and improve operational efficiency through data-driven solutions.
Contribute to a collaborative engineering culture focused on knowledge sharing, innovation, and continuous improvement.
Minimum Qualifications
Bachelor's degree, or equivalent practical experience, in Computer Science, Engineering, Information Systems, Mathematics, or another quantitative discipline.
Strong experience developing complex SQL queries for large-scale analytical workloads.
Experience designing and implementing data warehouse solutions, data models, and ETL/ELT pipelines.
Strong understanding of data modeling, data quality, metadata, and data lineage concepts.
Experience delivering end-to-end data engineering solutions from requirements through production deployment.
Excellent analytical and problem-solving skills with the ability to navigate ambiguous business problems.
Outstanding written and verbal communication skills with experience presenting technical concepts to both engineering teams and business leaders.
Demonstrated ability to collaborate effectively across cross-functional organizations.
Preferred Qualifications
Experience supporting cloud infrastructure, capacity planning, operations analytics, or large-scale distributed systems.
Experience developing self-service analytics platforms and reporting solutions.
Familiarity with modern data engineering technologies and cloud-native data architectures.
Experience working with large, complex datasets in fast-paced engineering organizations.
Passion for building trusted data products that enable strategic decision-making.
What You'll Bring
Successful candidates demonstrate:
Deep expertise in SQL and data engineering best practices.
Strong ownership and accountability for delivering high-quality solutions.
Curiosity to understand complex business domains and translate them into scalable data products.
The ability to explain technical concepts, data lineage, and analytical findings to diverse audiences.
A collaborative mindset with a commitment to continuous learning and operational excellence.
Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion
External Responsibilities
Responsibilities
Design, develop, test, validate, document, and maintain scalable data engineering solutions and self-service analytics platforms.
Build high-quality SQL-based data pipelines, curated datasets, and reusable data models that support reporting and analytical workloads.
Develop and maintain canonical datasets that serve as trusted sources for strategic and operational decision-making.
Partner with engineering, finance, product, and business stakeholders to understand requirements and translate complex business problems into scalable data solutions.
Own projects from requirements through production delivery, ensuring accuracy, maintainability, and operational excellence.
Clearly communicate data lineage, assumptions, business rules, and transformation logic to both technical and non-technical audiences.
Continuously improve data quality, governance, documentation, and engineering best practices.
Support the development of self-service reporting capabilities that empower stakeholders across OCI.
Identify opportunities to automate manual processes and improve operational efficiency through data-driven solutions.
Contribute to a collaborative engineering culture focused on knowledge sharing, innovation, and continuous improvement.
Minimum Qualifications
Bachelor's degree, or equivalent practical experience, in Computer Science, Engineering, Information Systems, Mathematics, or another quantitative discipline.
Strong experience developing complex SQL queries for large-scale analytical workloads.
Experience designing and implementing data warehouse solutions, data models, and ETL/ELT pipelines.
Strong understanding of data modeling, data quality, metadata, and data lineage concepts.
Experience delivering end-to-end data engineering solutions from requirements through production deployment.
Excellent analytical and problem-solving skills with the ability to navigate ambiguous business problems.
Outstanding written and verbal communication skills with experience presenting technical concepts to both engineering teams and business leaders.
Demonstrated ability to collaborate effectively across cross-functional organizations.
Preferred Qualifications
Experience supporting cloud infrastructure, capacity planning, operations analytics, or large-scale distributed systems.
Experience developing self-service analytics platforms and reporting solutions.
Familiarity with modern data engineering technologies and cloud-native data architectures.
Experience working with large, complex datasets in fast-paced engineering organizations.
Passion for building trusted data products that enable strategic decision-making.
What You'll Bring
Successful candidates demonstrate:
Deep expertise in SQL and data engineering best practices.
Strong ownership and accountability for delivering high-quality solutions.
Curiosity to understand complex business domains and translate them into scalable data products.
The ability to explain technical concepts, data lineage, and analytical findings to diverse audiences.
A collaborative mindset with a commitment to continuous learning and operational excellence.
Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion
