Oracle PL/SQL Developer with AI

Business Term and Definition Engineering Review strategic process inventory SPI PDFs business documents data dictionaries and metadata extracts to identify business terms and domain concepts Define clear business definitions for terms used by SPI users Identify synonyms abbreviations alternate names and commonly used phrases for each business term Distinguish between similar or overloaded terms that may map to different database structures depending on business context Maintain terminology consistency across the semantic layer and knowledge base repository Oracle Metadata Analysis Use Toad and Oracle metadata extracts to understand available schemas tables columns keys and relationships Analyze physical data structures and determine which tables and columns support each business term Identify candidate joins filters dimensions measures and identifiers needed to answer common SPI questions Work with the Data Architect to validate table relationships materialized views and performanceoptimized access paths TermtoData Mapping Create mappings from business terms to Oracle tables columns views and materialized views Ensure mappings are precise enough to support naturallanguagetoSQL generation Identify gaps where business terms lack clear physical data mappings Semantic Layer Buildout Support creation of the Talk to SPI semantic layer by organizing terms entities attributes metrics relationships and rules Document basic relationships between business entities and database entities Define earlystage business rules where required such as calculation logic filtering rules eligibility rules or default interpretation rules Collaborate with the AI Context Engineer to publish validated mappings into the Knowledge Base Repository Collaborate with the AI Platform Engineer to test whether published mappings are correctly consumed by the GenAI platform Validation and Testing Test sample naturallanguage questions against expected table and column mappings Validate whether generated SQL uses the correct SPI structures Document mapping issues ambiguous terms missing metadata and required SME clarifications Support iterative improvements based on testing SME feedback and GenAI query results Primary Skill Oracle SQL PLSQL Secondary Skill Data modelling and architecture Tertiary Skill Python

4 years in data engineering metadata engineering semantic layer development data analysis or business data mapping Handson experience working with Oracle database metadata Experience connecting business terminology to physical database structures Experience working with business documentation PDFs data dictionaries and technical metadata Exposure to naturallanguagetoSQL semantic modeling or AI context engineering is strongly preferred Programming Query Languages Strong SQL especially Oracle SQL Intermediate Python for metadata parsing document processing mapping automation and validation Working knowledge of YAML JSON for structured semantic and mapping artifacts Basic Markdown for documentation Optional familiarity with regular expressions for text extraction and term matching Systems Tools Oracle Database Toad for Oracle Python libraries for metadata and document processing Git or source control for managing mappings Excel or CSV for earlystage mapping inventories Knowledge base repository or semantic layer repository Desired Qualifications Experience with enterprise process management systems POP ARISSDAR Exposure to GenAI platforms and LLMbased enterprise solutions Knowledge of regulatory and compliancedriven data environments Experience with data catalog tools vector search graph database or RAG tooling