Data Engineer Ssr / Sr — Python, AWS, Terraform, Pinecone

Remote — Argentina, Colombia, México, Chile, Uruguay

Full‑time contract

March, 2026

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.

• 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

• 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

• 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

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