Principal Business Metrics Platform Development Engineer – Oracle Cloud

Oracle Database Developer

Oracle & Data Core (Mandatory): The candidate must demonstrate strong expertise in Oracle Database 19c and above, with advanced proficiency in SQL—covering CTEs, analytic functions, and window functions. Intermediate to advanced PL/SQL skills are required for developing packages, jobs, and robust exception handling. Hands-on experience with Materialized Views across all refresh modes (Fast, Complete, On Demand) is essential, as is proficiency with table partitioning strategies such as Range, Interval, and Hash. Proven experience using Data Pump (expdp/impdp) for data export and import is required. Familiarity with Oracle's JSON capabilities, including SODA Collections and Duality Views, is highly desirable. The role also demands strong debugging capabilities to identify and resolve data inconsistencies across schemas and between DEV, UAT, and PROD environments.

Cloud Technologies (Desirable): The candidate should have practical experience with cloud platforms such as Google Cloud Platform, Microsoft Azure, or Amazon Web Services. Experience with Oracle Cloud Infrastructure (OCI) is highly preferred, particularly with services like Autonomous Database and Object Storage. A solid understanding of cloud security—including IAM, compartments, and policy configuration—is required. Experience using DBMS_CLOUD and DBMS_CLOUD_PIPELINE for cloud-based data ingestion, automation, and orchestration is expected. Knowledge of Pre-Authenticated Requests (PARs), database cloning, environment refreshes, migrations, and production cutovers is considered a strong advantage.

Python for Data & Automation (Mandatory): The candidate must be highly proficient in Python, with demonstrable experience in data engineering and process automation. This includes advanced scripting for data processing, external service integration, and API consumption. Experience connecting Python applications to Oracle using the oracledb driver is required. The candidate must be capable of automating data ingestion from multiple external sources, performing data quality validations, executing cross-environment comparisons, and processing large datasets in formats such as CSV and JSON. Experience with cron or similar scheduling tools for running automated jobs is also required.

Artificial Intelligence & Machine Learning (Big Plus): Hands-on experience with AI and Machine Learning techniques is highly valued. The candidate should be familiar with implementing classification models, pattern analysis, and anomaly detection solutions. Experience applying predictive models to support business analytics and operational decision-making is a significant advantage. The ability to operationalize AI/ML outputs within production systems and data pipelines is also desired.

Data Visualization & Consumption (Mandatory): Strong experience in Oracle APEX is expected, including the development of dashboards, Interactive Reports, and Interactive Grids. The candidate must be comfortable consuming views and materialized views as primary data sources. Experience with Oracle Analytics Cloud for enhanced reporting and advanced analytics is highly desirable.

Operations: Proficiency with Git for version control and Jira for task and workflow management is required. The candidate must have operational experience across DEV, UAT, and PROD environments, including production support, hot fixes, incident response, and post-deployment validations. The role requires effective collaboration with distributed teams, particularly across Mexico and India.

Functional Profile (Key Competencies): The ideal candidate demonstrates strong analytical and logical reasoning abilities, with a solid foundation in data modeling. Exceptional attention to detail—especially concerning data consistency and quality—is essential. The role requires technical autonomy, sound decision-making, and effective communication with both technical and non-technical stakeholders. The candidate must be capable of owning end-to-end data processes, from ingestion through analytical delivery.

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