Lead Data Engineer - Advertising

Truelogic · Brazil, Brasil

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É uma vaga remota: contratam de Brasil.

A vaga não divulga o salário.

Pedem pelo menos 5 anos de experiência.

Publicada por Truelogic e vigente desde 30 de outubro de 2026.

Descrição da vaga

ABOUT TRUELOGIC

At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals.

Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference.

By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future.

OUR CLIENT

Our client is the only technology and creative network with a balance of 50% creative and 50% engineers. Their unique makeup makes us the place where CMOs, CTOs and CIOs come together to drive results for their businesses. They partner with their clients to redefine what is possible to create lasting impact and drive long-term growth.

JOB SUMMARY

We are seeking an experienced Lead Data Engineer to architect and build the scalable data infrastructure powering our real-time insights, predictive systems, and dynamic generative AI applications.

We need a true builder—someone whose expertise extends far beyond standard data migrations. The ideal candidate will take enterprise data lakes and warehouses out of their latent, static states and transform them into active, low-latency backends for real-time, agentic AI applications. As a product-minded technologist, you will translate business needs into elegant technical solutions, establish engineering best practices, and lay the foundation for a world-class data organization.

Working cross-functionally in a 50/50 Tech and Creative environment, you will have significant autonomy in technical decision-making and play a pivotal role in shaping our data strategy, engineering standards, and team culture.

RESPONSIBILITIES

  • Architect & Activate Data: Design, build, and scale high-throughput, low-latency data infrastructure connecting cloud data lakes/warehouses to dynamic AI backends and real-time agentic workflows.
  • Transform Latent Stores: Operationalize static data repositories into active context layers, vector engines, and memory systems for autonomous AI agents and downstream applications.
  • Real-Time & Event-Driven Pipelines: Build real-time ingestion, event-driven streaming, and retrieval pipelines (RAG, vector stores, operational databases) to feed live AI applications.
  • Technical Leadership & Standards: Establish data architecture standards, CI/CD, documentation, and data quality best practices while mentoring data engineers.
  • Cross-Functional Collaboration: Partner with Machine Learning Engineers, Product teams, Creative Directors, and agency stakeholders to translate client and business requirements into production-grade data APIs and schemas.
  • AI-Enabled Engineering: Leverage AI-powered coding, agentic engineering, and modern automated workflows to accelerate development and execution.

QUALIFICATIONS AND JOB REQUIREMENTS

  • 5+ years in Data Engineering: Demonstrated experience designing, building, and scaling data pipelines and cloud infrastructure from the ground up.
  • Beyond Data Migrations: Proven track record of activating data infrastructure for dynamic, real-time downstream applications rather than focusing solely on batch ETL/ELT or static warehousing.
  • Agentic & Real-Time AI Backends: Direct experience building data layers for real-time, event-driven applications, vector databases (e.g., Pinecone, Qdrant, Milvus, pgvector), or retrieval-augmented generation (RAG) at scale.
  • Deep Cloud Expertise: Strong experience with major cloud platfor

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