Oracle SQL/PL Developer
Key Responsibilities
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
Analyse 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 performance optimized access paths
Term to Data Mapping
Create mappings from business terms to Oracle tables columns views and materialized views
Ensure mappings are precise enough to support natural language to SQL 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 early stage 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 natural language 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
Required Qualifications
Experience
4 years in data engineering metadata engineering semantic layer development data analysis or business data mapping
Hands-on 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 natural language to SQL semantic modelling 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 early stage mapping inventories
Knowledge base repository or semantic layer repository
Desired Qualifications
Experience with enterprise process management systems POP ARISSDAR
Exposure to GenAI platforms and LLM based enterprise solutions
Knowledge of regulatory and compliance driven data environments
Experience with data catalog tools vector search graph database or RAG tooling
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