Senior Level SQL Annotator at Odixcity Consulting

Job Summary

• We are seeking an experience senior python Developer to architect, build, and maintain high-performance backend systems and APIs.
• In this role, you will lead technical design decisions, write clean and scalable production code, and mentor junior engineers while collaborating with cross-functional teams to deliver robust software solutions.

Responsibilities

• Review, annotate and evaluate AI-generated SQL responses for correctness, clarity, query logic, joins, syntax, performance, security, and readability.
• Create detailed prompts and reference solutions to guide AI learning on complex data challenges.
• Assess solutions for accuracy, adherence to prompts, and identify errors in methodology, query structure, indexing strategy, or conceptual understanding.
• Deliver clear, constructive feedback and detailed technical explanations to support continuous model improvement.
• Run and validate proof-of-work code, fact check data-related claims, and rate/compared AI responses based on reasoning quality.
• Build automated SQL audit queries that can scan the annotated dataset daily to flag duplicates, conflicting labels, null values, or out of distribution samples before they reach the ML Team.
• Partner with ML Engineers to test proposed annotation guidelines against actual database records.

Requirements

• 7+ years of professional experience working with SQL in production with SQL in production environments as a Database Engineer, SQL Developer, Data Engineer, or similar role.
• Bachelors’ degree or higher in computer science, information systems, Engineering, mathematics, or a related technical field
• Expert-level proficiency in SQL, including complex joins, windows functions, aggregation strategies, query plan analysis, and performance tuning.
• Hands-on experience designing relational data models, schemas, and data warehouse structures (star and snowflake schemas).
• Exceptional written and spoken English (c1 level or higher) with the ability to write clear technical explanations,
• A methodical, systematic approach to evaluating reasoning quality and identifying subtle data or query issues.