ImplementationDataEngineer

This role is open to candidates based in LATAM, Africa, and Eastern Europe. Please note that as this role supports U.S.-based clients, candidates must be available to work during U.S. business hours aligned with the client’s time zone.   Client Overview Our client is a fast-growing AI-powered marketing intelligence platform that helps brands and retailers make smarter media investment decisions through advanced forecasting and attribution modeling. Their engineering team operates at the intersection of data infrastructure and machine learning, building the pipelines and models that power real commercial decisions for some of the most recognizable names in retail and ecommerce. They move quickly, hold high standards for code quality, and give engineers the autonomy to own their work end-to-end — from the first line of code to a clean handoff with full documentation. Role Overview The Implementation Data Engineer is the dedicated technical owner for new client onboarding, responsible for building the customer-specific ELT pipelines, dbt models, and Dagster orchestration that transform a freshly-signed account into a fully modeled, analytics-ready environment. This role sits at the core of the client delivery workflow, partnering closely with the Implementation Project Manager while maintaining full ownership of the technical build. The Implementation Data Engineer works within a modern analytics engineering stack and is expected to deliver independently, surface blockers early, and hand off completed onboardings with clean documentation and monitoring in place. Location Fully Remote (Work from Home) | 9AM - 5PM EST   Key Responsibilities Client Onboarding & Pipeline Development - Build and maintain scalable, fault-tolerant ELT pipelines for new client onboarding using Python - Develop and optimize dbt models, tests, and documentation following analytics engineering best practices - Orchestrate and monitor onboarding workflows using Dagster - Model clean, analytics-rea