• Recolectar datos de diversas fuentes, incluyendo bases de datos, archivos CSV y APIs, utilizando herramientas ETL para realizar limpieza y preprocesamiento. Eliminar valores atípicos, gestionar nulos y preparar datos para análisis eficiente. • Diseñar y construir pipelines de datos eficientes utilizando herramientas como Matillion, garantizando la automatización en la recolección, transformación y carga (ETL) de datos. • Integrar y consumir datos de APIs externas para enriquecer conjuntos de datos y mejorar la calidad de la información. • Contribuir al diseño de arquitecturas eficientes para el manejo de grandes volúmenes de datos, utilizando tecnologías como Python y SQL.

Location: Remote — Argentina, Colombia, México, Chile, Uruguay Job Type: Full-time contract Date Posted: March, 2026 Project Brief We're building a cloud-native data infrastructure powering AI-driven products — from ingestion pipelines and vector search to MCP-based integrations and multi-tenant architectures. You'll own the design, deployment, and reliability of data pipelines end-to-end, working across AWS, Terraform, and Pinecone in a fast-moving environment where architectural decisions matter and ownership is real. Must-Haves - Strong Python skills — Lambda functions, scripting, API consumption, and data processing pipelines - Hands-on AWS experience across: Lambda, S3, API Gateway, ECS/Fargate, Secrets Manager, Cognito, CloudWatch, and SQS + DLQ - Terraform for infrastructure-as-code — remote state with S3 + DynamoDB, modular resource definitions, and multi-environment management - Docker — containerization, Dockerfile hardening, and ECS task image builds - Pinecone — index creation, namespace design for multi-tenancy, metadata schema, upsert logic, and hybrid search configuration - Experience with embedding models and ETL/data transformation pipelines - MCP protocol experience — FastMCP SDK, Streamable HTTP transport, tool definition - REST API consumption — Cognito-authenticated requests, response parsing, and S3 persistence - Git/GitHub — trunk-based branching, semantic PRs, and branch-per-feature workflows - JSON schema design for pipeline service contracts and API response structures - Retry and error handling patterns — exponential backoff and failure architecture - Clear English communication and ability to work independently with minimal supervision Nice to Have - Incremental update and change detection logic for pipeline efficiency - CloudWatch alarm design and pipeline health dashboards - Content-hash deduplication for embedding cost optimization - Lambda memory and concurrency tuning - VPN site-to-site configuration - LangChain / LangGraph experience - Prompt engineering fundamentals - GitHub Actions — CI/CD pipeline setup and deployment automation - Marketing Business Acumen What You Will Do - Design, build, and maintain cloud-native data pipelines across AWS Lambda, S3, ECS/Fargate, and SQS - Manage and evolve infrastructure-as-code using Terraform across multiple environments - Build and optimize vector search workflows in Pinecone — including multi-tenant namespace design, metadata schemas, and hybrid search - Develop and improve MCP server integrations using FastMCP SDK and Streamable HTTP transport - Implement and harden authentication flows using AWS Cognito and Secrets Manager - Monitor pipeline health via CloudWatch — log groups, alarms, and observability for Lambda and ECS - Apply cost modeling discipline — flag and mitigate high-cost operations (e.g. embedding calls at scale) - Work within an established SA governance model, contributing to architectural decisions with clear documentation and standards - Collaborate with engineering and applied science teams to deliver reliable, scalable data infrastructure Why This Could Be Your Next Big Move - 🧱 Own the data foundation — You're not maintaining legacy systems. You're designing the infrastructure that AI products are built on top of. - 🤖 Work at the AI/data intersection — Vector search, embeddings, MCP integrations, and multi-tenant architectures. This is where data engineering and AI meet. - ☁️ Deep AWS stack — Lambda, ECS, Cognito, SQS, Secrets Manager and more — a real opportunity to broaden and deepen your cloud expertise across a full production stack. - 🔝 High ownership, high impact — Fast-moving environment where your architectural decisions shape the product directly, with visibility across the entire engineering org. Benefits & Compensation - 💵 $[3,500] – $[5,000]/month — paid in USD, bi-weekly via Deel - 🌎 Fully Remote — work from anywhere in Latin America - 📄 Full-time contract with a U.S. company — 6-month initial term, full-time conversion - 🏖️ Paid PTO — competitive package, grows with tenure - 🤝 Referral Program — earn a bonus for referring talent that gets hired To Apply Please send your resume in English. Include the following depending on your role: - 🔗 LinkedIn Profile URL (required) - 💻 GitHub Portfolio or code samples — show us your pipeline and infrastructure work (required) - ✉️ Cover Letter — tell us about a data pipeline or cloud architecture you built and the impact it had (optional but encouraged) About OneSeven Tech Founded by James Sullivan, OneSeven Tech is a premier digital product agency serving startups and enterprises. Our clients have collectively raised over $100M in VC, and our enterprise partners include 2,000+ person hospitality groups and NASDAQ-listed companies. We work fully remote, move fast with 1-week sprints, and focus on elegant solutions to complex problems. Salary: 3500 - 5000 USD Per month

¡Trabaja en DaCodes! Somos una firma de expertos en software y transformación digital de alto impacto. Durante 10 años hemos creado soluciones enfocadas en la tecnología e innovación gracias a nuestro equipo de casi 300 talentosos #DaCoders, incluyendo desarrolladores, arquitectos, diseñadores UX/UI, PMs, QA testers y más. Nuestro equipo colabora en proyectos con clientes en LATAM y Estados Unidos, logrando resultados sobresalientes. En DaCodes, tendrás la oportunidad de impulsar tu desarrollo profesional, trabajar en diversos proyectos dentro de distintas industrias, y contribuir al diseño, implementación y optimización de infraestructuras en la nube. Nuestros DaCoders tienen un gran impacto en el éxito de nuestro negocio y el de nuestros clientes. Serás el experto que participará en nuestros proyectos y tendrás acceso a startups disruptivas y marcas globales. ¿Te interesa? Buscamos un Data Solutions Engineer con perfil técnico híbrido, capaz de desenvolverse tanto en el desarrollo de software como en la construcción de soluciones de datos modernas. Este rol combina mantenimiento de sistemas existentes, desarrollo de nuevos componentes y la implementación de pipelines de datos utilizando tecnologías como Microsoft Fabric y Databricks. Es ideal para alguien con mentalidad práctica, orientado a la ejecución, que pueda moverse con soltura entre entornos legacy y procesos de modernización tecnológica. Tendrás un rol activo en la construcción de soluciones end-to-end, colaborando con equipos técnicos y de negocio para resolver problemas reales mediante tecnología.

• Upload and organize patient records from multiple data sources (CSV, spreadsheets, clinical documents) • Prepare and structure large datasets for system migration • Ensure accurate and efficient data transfer into the platform • Clean and standardize datasets from external systems • Identify missing, duplicate, or inconsistent data • Normalize formats (names, dates, medical data) • Validate data accuracy before and after migration • Utilize AI tools to extract and process patient data • Generate structured patient records • Review and validate AI-generated outputs for accuracy • Perform detailed QA checks to ensure near-zero error rates • Identify and resolve issues proactively before they impact implementation • Maintain high standards of data integrity and consistency • Update implementation trackers and progress reports • Communicate updates, blockers, and issues clearly with the team.