Senior Full Stack Software Engineer

Senior Full Stack Software Engineer / Platform Architect Nationwide, Colombia | Posted on 01/21/2026 We are seeking a Senior Full‑Stack Software Engineer / Platform Architect to address critical short‑term and long‑term platform gaps across product categorization, data acquisition, and cloud architecture. While much of the core sustainability data modeling has already been completed, the current platform suffers from disconnects between how products are categorized, specified, and purchased versus how data is stored and processed, as well as an overreliance on Google Sheets–based workflows that are no longer scalable. This role will focus first on product categorization and ingestion architecture, then lead the migration of data and pipelines from Snowflake to Google Cloud (CloudSQL + Big Lake) to align data storage, processing, ETL, and AI capabilities in a single, cohesive GCP‑native stack alongside Cloud Run and Vertex AI Studio. This is a hands‑on, execution‑oriented role for someone who can operate across application code, data systems, and cloud infrastructure. Near‑Term Priority (First 3–6 Months) 1. Product Categorization & Data Intake (Immediate Need) Design and implement robust product categorization and taxonomy support, aligned with how products are promoted and specified, how they appear in bids, specs, and POs, and how sustainability attributes are applied and scored. Replace brittle Google Sheets–based ingestion workflows with structured APIs, validated, versioned storage. Ensure categorization logic is maintainable and compatible with downstream scoring and analytics. Core Responsibilities Lead the migration from Snowflake to Google CloudSQL and BigLake. Design a unified architecture where core application data lives in CloudSQL, analytical and scoring data lives in BigLake, and ETL/data movement is tightly coupled with Cloud Run services. Ensure data locality with Cloud Run (ETL + backend services; Matillion replacement). 3. Full‑Stack Application Development Build backend services to support product ingestion and categorization, validation and lifecycle management, and design APIs that replace spreadsheets as the system of record. Partner with frontend developers (or contribute directly) to enable internal tools for auditors and account managers, structured data entry and review workflows. Design application‑driven ETL patterns rather than warehouse‑first ETL, ingest product and audit data, scoring algorithms, analytics and reporting layers. Support future AI‑driven extraction pipelines feeding directly into CloudSQL / BigLake. 5. AI & Automation Enablement (Platform‑Level) Ensure the platform is designed to support confidence scoring and human review, feedback loops for continuous improvement. Work closely with data engineers and ML engineers using Vertex AI. Requirements Required Skills & Experience Strong experience building backend systems in modern languages (e.g., Python, TypeScript, Java, or Go). Experience designing APIs and services that replace manual or spreadsheet‑based workflows. Comfort working across application logic and data persistence layers. Data & Cloud Architecture Experience migrating off a data warehouse (Snowflake or similar) to cloud‑native storage. Hands‑on experience with BigLake / BigQuery and strong understanding of transactional vs. analytical data separation. Data Modeling (Applied, Not Greenfield) Ability to extend and adapt existing data models rather than redesign from scratch. Experience aligning data structures with real‑world product and procurement workflows. AI Readiness Experience building platforms adjacent to AI/ML systems. Familiarity with Vertex AI or similar platforms, document intelligence and extraction workflows, understanding of how to structure data for downstream ML consumption. What This Role Is Not Not a research‑focused ML role. Not a Snowflake optimization role. This is a build‑and‑fix‑now role for someone who can move fluidly between code, data, and cloud infrastructure. What Success Looks Like Google Sheets are no longer a core system of record. Product categorization is explicit, structured, and enforceable. Data lives natively in GCP, close to CloudRun and Vertex AI. Snowflake is deprecated or eliminated. End‑to‑end data acquisition (documents → structured data → scoring → analytics) is finally tractable. Competitive Salary: Get paid what you're worth Prepaid Medicine: Your health is our priority Life Insurance: Peace of mind for you and your loved ones Birthday Day Off: Celebrate your special day YOUR way Indefinite‑Term Labor Contract: Stability and all legal benefits included #J-18808-Ljbffr