Lead Data Engineer - Advertising

BrazilRemoteFull-timelead

Data EngineerData

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Requirements Summary

At least 5 years of experience in Data Engineering, with a proven track record of designing and scaling data pipelines and cloud infrastructure from the ground up. Experience building a

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Data EngineerData

We are looking for a senior, product-minded Data Engineer to architect and build scalable data infrastructure that powers real-time insights, predictive systems, and generative AI applications. In this leadership role, you will transform traditional data lakes and warehouses into active, low-latency data platforms supporting intelligent applications and autonomous AI agents. You will design event-driven pipelines, develop advanced retrieval systems, and establish robust engineering practices. Working closely with Machine Learning, Product, and Creative teams, you will translate complex business needs into production-ready technical solutions. You will also shape data strategy, mentor engineering talent, and help build a high-performing data organization within a collaborative, technology-driven environment.

Architect, build, and scale high-throughput, low-latency data infrastructure connecting cloud data lakes and warehouses to real-time AI applications.
Transform static data repositories into active context layers, vector engines, and memory systems for autonomous AI agents.
Develop real-time ingestion, event-driven streaming, and retrieval pipelines, including RAG architectures, vector stores, and operational databases.
Build and optimize data backends that support predictive systems, generative AI applications, and agentic workflows.
Establish data architecture standards, CI/CD practices, documentation, and data quality processes.
Mentor data engineers and promote engineering excellence and knowledge sharing.
Collaborate with Machine Learning Engineers, Product teams, Creative Directors, and other stakeholders to translate business requirements into production-grade data APIs and schemas.
Leverage AI-assisted development tools, agentic coding, and automated engineering workflows to accelerate delivery.
Contribute to technical strategy, architectural decisions, and the development of a world-class data engineering organization.

Requirements

~1 min read

At least 5 years of experience in Data Engineering, with a proven track record of designing and scaling data pipelines and cloud infrastructure from the ground up.
Experience building and activating data infrastructure for dynamic, real-time applications, beyond traditional batch ETL/ELT processes and static data warehousing.
Hands-on experience developing real-time, event-driven data layers for AI applications.
Experience with vector databases such as Pinecone, Qdrant, Milvus, or pgvector, and large-scale Retrieval-Augmented Generation (RAG) systems.
Strong expertise in major cloud platforms, including AWS, GCP, or Azure.
Experience with modern cloud data platforms such as Snowflake, Databricks, or BigQuery.
Advanced proficiency in Python and SQL for data processing and real-time pipeline development.
Familiarity with AI-assisted development tools, agentic coding, and automated engineering workflows.
Demonstrated ability to mentor engineers, establish technical standards, and drive engineering best practices.
Excellent communication and collaboration skills, particularly in cross-functional technology and creative environments.
Based in Latin America.
Fluent in English.