Senior AI Data Engineer - QSR Enterprise
S
SantexQuick Service Restaurant
LATAMFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLAirflowRESTful APIsdbt
Requirements
- 5+ years of experience in data engineering
- Strong SQL skills
- Strong Python skills
- Experience building ingestion pipelines from APIs, streaming, and batch sources
- Experience with cloud data platforms and modern data stack
- Experience with POS or operational data systems preferred
- Familiarity with Agentic development tools such as Codex, Cursor or Claude Code
- Experience in QSR or retail environments
- Experience integrating vendor systems (labor, inventory, finance)
- Familiarity with semantic layers and metadata tools
- Experience enabling data for AI/LLM use cases
Responsibilities
- Design and build ingestion pipelines for POS systems across global markets (transactions, orders, payments, speed of service)
- Integrate data from back-office vendor systems (labor scheduling, inventory, supply chain, finance)
- Handle diverse ingestion patterns (batch, streaming, APIs, file-based ingestion)
- Normalize and standardize data across vendors, regions, and brands
- Ensure data freshness, completeness, and consistency across all ingestion pipelines
- Manage vendor-specific schemas and evolving data contracts
- Build scalable ELT/ETL pipelines using modern tools (DBT, Airflow, etc.)
- Support real-time and batch processing for operational and analytical use cases
- Optimize ingestion pipelines for performance, reliability, and cost
- Ensure high availability across global data workloads
- Build data models supporting standardized KPIs (same-store sales, speed of service, traffic, labor productivity)
- Align ingested raw data with business-friendly semantic abstractions
- Support both governed (manual) and AI-driven semantic approaches
- Capture metadata, lineage, and schema details from ingestion pipelines
- Enable AI systems using structured context (metadata, lineage, example queries)
- Ensure AI systems can reliably interpret POS and operational data
- Implement validation and monitoring for ingestion pipelines
- Ensure data accuracy across POS and vendor systems
- Support governance for consistent metric definitions across regions
- Maintain versioning and schema evolution processes
View Full Description & ApplyYou'll be redirected to the employer's site
