Data Engineer
About The Position
Cargomatic is seeking a Senior Data Architect – Data Engineering to design and build scalable, cloud-native data infrastructure that powers analytics, machine learning, and AI-driven applications. This role combines deep data architecture expertise with hands-on experience in modern data platforms and LLM-enabled application development. You will lead the design of enterprise-grade data models, architect RAG systems, implement agentic workflows, and integrate secure, production-ready LLM capabilities into our ecosystem. This is a high-impact role with significant ownership, visibility, and opportunity to shape the future of intelligent logistics technology.
Requirements
- Bachelor’s degree in Computer Science or equivalent practical experience
- 8+ years of software or data engineering experience in production environments
- Strong expertise in data modeling, distributed systems, and scalable cloud architectures
- Hands-on experience with ETL/ELT frameworks and streaming technologies (Kafka, Spark, HEVO, Snowflake, DBT, etc.)
- Advanced SQL skills and deep understanding of modern storage formats
- Proficiency in Python and RESTful API development
- Experience integrating LLM APIs into production applications
- Strong understanding of system reliability, observability, and cost management in cloud environments
Nice To Haves
- Experience building RAG pipelines including embeddings, vector search, chunking strategies, and hybrid retrieval
- Experience designing multi-agent or agentic AI workflows with orchestration frameworks
- Knowledge of LLM evaluation, monitoring, and tracing tools (LangSmith or similar)
- Experience with microservices architecture and distributed system design
- Exposure to transportation, logistics, or supply chain domains
- Active GitHub contributions or demonstrated passion for emerging AI and data technologies
Responsibilities
- Design and build scalable, cloud-native data pipelines (batch and streaming) supporting analytics, ML, and AI-powered applications
- Architect enterprise-grade data models across data lakes, warehouses, and real-time systems (Snowflake, Databricks, Kafka, DBT)
- Define standards for data governance, reliability, performance, and cost optimization
- Optimize storage formats and distributed data systems (Parquet, Delta Lake, Iceberg)
- Develop Retrieval-Augmented Generation (RAG) systems integrating structured and unstructured enterprise data
- Design and implement agentic workflows using frameworks such as LangChain, LangGraph, LlamaIndex, n8n, or similar
- Integrate LLM APIs (OpenAI, Anthropic, or similar) into secure, production-ready applications
- Implement guardrails, validation layers, monitoring, and evaluation frameworks to mitigate hallucination, prompt injection, and data security risks
- Build secure backend APIs (Python/FastAPI) to expose AI-powered capabilities
- Ensure observability, monitoring, and cost controls across AI and data services
- Contribute to microservices architecture and distributed system design
- Partner cross-functionally with Product, Engineering, and Operations to translate business requirements into scalable technical solutions
- Mentor junior engineers and contribute to architectural standards and best practices
- Drive innovation in data engineering and AI-powered logistics systems
Benefits
- Medical, Dental, and Vision insurance
- 401(k) with company match
- Flexible Spending Accounts (FSA)
- Company-paid Life and Disability insurance
- Flexible Paid Time Off (PTO) and company holidays
- Paid Parental Leave
- Employee Assistance Program (EAP)
- Opportunity to build cutting-edge AI solutions in a high-growth logistics technology company
- Collaborative, high-impact team environment
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
