Senior Data Engineer

About the role

Engagement Type: Full-Time / Contractor

Location: Latin America | 100% Remote

About CodeRoad

CodeRoad is a technology execution partner trusted by companies across North America since 2002. We work alongside our clients to engineer, modernize, and scale the technology that powers their businesses, combining deep technical expertise, specialized teams, and shared accountability for outcomes. Our capabilities span product engineering, platform engineering, legacy modernization, and AI engineering.

Our engineers, designers, delivery leaders, and technology specialists collaborate through Velocity Studios: specialized teams developed within CodeRoad to deliver complex technology initiatives. Being assigned to a project means you become part of a collaborative environment where you can strengthen your expertise, take ownership of meaningful work, and grow alongside experienced professionals.

Why Build Your Career at CodeRoad?

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High-Velocity Work & Client Exposure: We work close to the technology, teams and roadmaps that move real outcomes. Direct engagement with U.S. client teams and roadmaps.

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Career Continuity & Long-Term Opportunity: Your career here can outlast any single project. Continuous multi-project pipeline; long-tenure CodeRoaders.

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Engineering Autonomy & Technical Mastery: We invest in the skills that shape what's next. Agentic AI tools and training, Coursera Enterprise, Studio practice labs, L1-L7 Career Framework.

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High-Trust Employee Experience: You grow in an environment built on trust, transparency and recognition. High-touch onboarding, transparent leadership communication, community recognition, psychological safety.

Key Responsibilities

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Architect Semantic & Data Layers: Design and implement modern semantic models (facts, dimensions, and metric stores using tools like dbt) to abstract complex operational databases for AI querying and analytical consumption.

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Build Scalable Data Pipelines: Construct curated, high-performance analytical views and production ELT/ETL pipelines that streamline data retrieval, enhance freshness, and eliminate redundancy across environments.

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Optimize Low-Latency Performance: Tune complex database queries, indexing, and schema definitions through systematic query log analysis to support demanding analytical and AI workloads.

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Implement Robust Governance & Security: Lead the rollout of granular data governance, including Role-Based Access Control (RBAC), Row-Level Security (RLS), dynamic data masking, and anonymization for PII protection.

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Enable Agentic AI & RAG Ecosystems: Collaborate directly with cross-functional AI engineering teams to align data structures, semantic foundations, and retrieval mechanisms with Retrieval-Augmented Generation (RAG) and Agentic AI workflows.