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Data Architect

1 month ago

Little Rock, Arkansas, United States Oracle Full time
Job Description

The Oracle Cloud Infrastructure Compute team is seeking a highly skilled Data Architect to design and build scalable high-throughput ETLs and robust data-marts. As OCI continues to scale to meet the demands of an ever-growing customer base and regions, we need an architect who can lead data-driven initiatives to ensure OCI provides an outstanding customer experience while continuously improving the efficiency of development processes.

The ideal candidate is someone who thrives in the face of ambiguity and can quickly distill abstract ideas into concrete solutions, with a proven track record of delivering complex business intelligence and reporting solutions across a highly complex environment involving multiple organizations, departments, and teams.

Responsibilities
  • Design and lead implementation of scalable data solutions: critical data feeds for OCI Compute fleet that power our reports, dashboards, and analytics.
  • Perform data modeling and integration activities in data warehouse systems.
  • Define and implement business data reporting and analysis requirements.
  • Coordinate with business units to identify new data requirements, analysis strategies, and reporting mechanisms.
  • Support the development of business intelligence standards to meet business goals.
  • Train and guide junior engineers in data reporting and analytical skills.
  • Recommend enhancements and modifications to optimize business intelligence processes.
  • Write high-quality SQL queries to retrieve and analyze data from database tables (e.g., Oracle, MySQL).
  • Troubleshoot code, research root causes, document solutions, and communicate to all stakeholders.
  • Track reporting and production anomalies.
  • Ensure data is within required quality standards.
  • Keep stakeholders informed about problems and resolutions.
  • Deliver products on schedule and communicate updates regularly.

The ideal candidate should have substantial experience (around 12+ years) in data engineering, especially with large data sets (e.g., handling 300 million rows per hour). Experience in scalable frameworks like Python, Spark, Kubernetes, Kafka, and working with data warehouses and data lakes is crucial.

The focus will be on leading, architecting, designing, and driving the implementation of these systems.

BS (or higher) in Computer Science or related engineering fields.