Data Engineer

• Design module content for the Fintech Engineering Specialization at Jala University
• Create labs
• Develop a reference implementation
• Build an evaluation harness
• Prepare an instructor guide

Academic Content Developer – Financial Data Engineering, Credit Systems

• Diseñar, desarrollar y mantener dashboards en Power BI
• Asegurar la concordancia, calidad y alineación de los datos reportados
• Personalizar dashboards según las particularidades y necesidades
• Gestionar el flujo completo de datos: gobierno de datos, ETL y visualización
• Asegurar calidad, consistencia y trazabilidad desde la ingesta hasta el dashboard final
• Mantener, refactorizar y evolucionar sistemas heredados
• Crear automatizaciones, microservicios y algoritmos personalizados
• Optimizar el procesamiento y análisis de datos
• Documentar procesos, flujos de datos, criterios de calidad y lineamientos de personalización
• Asegurar continuidad operativa y escalabilidad

• Diseñar, desarrollar y mantener dashboards en Power BI
• Asegurar la concordancia, calidad y alineación de los datos reportados
• Gestionar el flujo completo de datos: gobierno de datos, ETL y visualización
• Asegurar calidad, consistencia y trazabilidad desde la ingesta hasta el dashboard final
• Mantener, refactorizar y evolucionar sistemas heredados
• Crear automatizaciones, microservicios y algoritmos personalizados
• Optimizar el procesamiento y análisis de datos
• Documentar procesos, flujos de datos, criterios de calidad y lineamientos de personalización
• Asegurar continuidad operativa y escalabilidad

• Develop, optimize, and maintain secure HR data pipelines using dbt, PySpark, Python, and Apache Airflow
• Ingest HR data from REST APIs, real-time streams, Google Sheets, web APIs, and external platforms
• Provision, configure, and maintain scalable extraction, transformation, and loading infrastructure using Terraform, AWS Glue, AWS EMR, and AWS S3
• Design and maintain data models, data marts, and warehouse structures in Snowflake and Google BigQuery
• Build semantic views and ontology layers mapping CORE → SEMANTIC → METRICS on dbt models
• Configure and deploy generative AI query agents using Snowflake Cortex Analyst and Cortex Search
• Maintain MCP connections between Snowflake and internal AI tools
• Monitor pipelines to enforce 99.5% uptime
• Build automated tests within a Data Quality Framework
• Ensure secure handling of PII and produce comprehensive technical documentation
• Support workforce analytics for international enterprise Centers of Excellence and executive leadership

• Design, model, and maintain complex data structures across MS SQL Server and MongoDB
• Resolve data quality issues
• Write complex queries and develop stored procedures
• Perform indexing and query performance tuning
• Execute automated pipeline deployments and migrate schemas into production
• Apply agile methods and continuous delivery concepts
• Build and maintain secure, high-performing data pipelines and APIs using REST and JSON
• Drive test strategies and test automation
• Ship, maintain, and troubleshoot production software products
• Collaborate with diverse teams on international client projects
• Participate in ceremonies, stand-ups, and collaborative sessions aligned with Central Time

Senior Data Engineer

• Build, maintain, and enhance production ETL pipelines connecting REST APIs with GCP-based data warehouse environments
• Develop and maintain data integration components using TypeScript/Node.js and Python within an existing pipeline architecture
• Develop data pipelines using BigQuery, Cloud Storage, Dataflow, and Pub/Sub
• Implement transformation logic for billing events, subscription lifecycle data, revenue data, and other data flowing into the GCP data warehouse
• Develop and maintain REST API integrations, including authentication, pagination, error handling, retries, and reliable data extraction
• Support pipeline monitoring and reliability through alerting, logging, error handling, retry mechanisms, and data quality checks
• Write complex SQL queries for source-to-warehouse data validation, reconciliation, and parity checks
• Collaborate with architecture stakeholders on warehouse-level validation requirements and translate them into SQL checks and reconciliation logic
• Investigate and resolve data pipeline, integration, transformation, and data quality issues
• Follow established coding standards, architecture patterns, CI/CD workflows, and development practices within the existing codebase
• Collaborate with Data Engineering leadership for technical direction while maintaining ownership of assigned development work
• Provide clear written status updates, surface blockers early, and communicate progress effectively within an async-first distributed team
• Contribute to Agile/Kanban workflows while remaining focused on hands-on engineering execution

Data Engineer jobs in Peru

Academic Content Developer – Financial Data Engineering, Credit Systems

Data Engineer

Data Engineer

Data Engineer

Senior Data Engineer

Senior Data Engineer, GCP, Data Integration