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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 .
Core Competencies
Role fitCore 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 advanced data engineering practices and cloud technologies. Proficient in mentoring teams and establishing data architecture standards while utilizing AI-assisted development tools.
Highest-signal resume keywords
Data Pipeline DesignCloud Infrastructure ExperienceVector Database ProficiencyAdvanced Python ProficiencyStrong Communication Skills
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringData Architecture StandardsEvent-Driven ApplicationsRetrieval-Augmented GenerationPythonSQLCI/CDData Quality Best PracticesAI-Assisted DevelopmentAutomated Engineering Workflows
Soft Skills
MentoringExceptional Communication
Tools & Technologies
AWSGCPAzureSnowflakeDatabricksBigQueryPineconeQdrantMilvusPgvector
Industry Keywords
Cloud Data LakesReal-Time WorkflowsDynamic AI BackendsData APIsOperational Databases
Tech Stack
Tools & technologiesAWSAzureBigQueryCloudGoogle 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, or Azure
- Experience with Snowflake, Databricks, or BigQuery
- Advanced proficiency in Python and SQL
- Experience utilizing 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
- Work with Autonomy
- Work with Top American Companies
- Engagement activities
- Work-life balance support
- Access to a diverse, global professional network
- Collaboration with multicultural teams
- Work alongside senior, seasoned professionals