Lead Data Engineer – Advertising

Truelogic Software

. Design, build, and scale high-throughput, low-latency data infrastructure connecting cloud data lakes and warehouses to dynamic AI backends and real-time agentic workflows .

Posted 10/31/2026full-timeRemote • MexicoSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and scaling data infrastructure for real-time applications, leveraging cloud platforms and advanced data engineering practices. Proficient in mentoring teams and establishing data architecture standards while ensuring high data quality and operational efficiency.

Highest-signal resume keywords

Data EngineeringData Pipeline DesignCloud Infrastructure (AWS, GCP, Azure)Vector Databases (Pinecone, Qdrant, Milvus, pgvector)Python and SQL Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignCloud InfrastructureVector DatabasesRetrieval-Augmented Generation (RAG)PythonSQLEvent-Driven ApplicationsData Architecture StandardsCI/CDData Quality Best Practices

Soft Skills

MentoringExceptional Communication Skills

Tools & Technologies

AWSGCPAzureSnowflakeDatabricksBigQueryAI-Assisted Development Tools

Industry Keywords

Data InfrastructureReal-Time ApplicationsDynamic AI BackendsOperational DatabasesCloud Data LakesData Repositories

Tech Stack

Tools & technologies

AWSAzureBigQueryCloudGoogle Cloud PlatformPythonSnowflakeSQL

About the role

Key responsibilities & impact

Design, build, and scale high-throughput, low-latency data infrastructure connecting cloud data lakes and warehouses to dynamic AI backends and real-time agentic workflows
Operationalize static data repositories into active context layers, vector engines, and memory systems for autonomous AI agents and downstream applications
Build real-time ingestion, event-driven streaming, and retrieval pipelines including RAG, vector stores, and operational databases
Establish data architecture standards, CI/CD, documentation, and data quality best practices
Mentor data engineers
Partner with Machine Learning Engineers, Product teams, Creative Directors, and agency stakeholders
Translate client and business requirements into production-grade data APIs and schemas
Leverage AI-powered coding, agentic engineering, and modern automated workflows

Requirements

What you’ll need

5+ years in Data Engineering
Experience designing, building, and scaling data pipelines and cloud infrastructure from the ground up
Experience activating data infrastructure for dynamic, real-time downstream applications
Experience building data layers for real-time, event-driven applications
Experience with vector databases such as Pinecone, Qdrant, Milvus, or pgvector
Experience with retrieval-augmented generation (RAG) at scale
Strong experience with AWS, GCP, and/or Azure
Experience with Snowflake, Databricks, and/or BigQuery
Advanced proficiency in Python and SQL
Experience using AI-assisted development tools, agentic coding, and automated engineering workflows
Track record of mentoring engineers and setting engineering standards
Exceptional communication skills
Located in Latin America
Fluent in English

Benefits

Comp & perks

100% remote work
Highly competitive USD pay
Paid time off
Autonomy in managing work time
Opportunity to work with top American companies on innovative, high-impact projects
Engagement activities
Work-life balance support
Collaboration with a diverse, global network
Collaboration with seasoned senior professionals