Data Engineer

Senior Data Architect – Data Engineering

Location: San Francisco, CA
Reports To: VP of Engineering
FLSA Status: Exempt
Employment Type: Full-Time
Compensation: $140,000 – $160,000 annually (based on experience)

About Cargomatic

Cargomatic is transforming the local trucking industry with cutting-edge technology that connects shippers and carriers in real time. Every product that humans build, grow, or sell has spent time on a truck. Local trucking is the lifeblood of every regional economy, yet this $82 billion industry still relies heavily on outdated systems. Cargomatic is bringing transparency, efficiency, and intelligence to local freight through modern technology and data-driven solutions.

We are solving complex, real-world logistics problems every day. If you thrive in a fast-paced environment, enjoy building scalable systems, and want to help shape the future of AI-powered logistics, we’d love to meet you.

Position Summary

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.

Key Responsibilities

Data Architecture & Engineering

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  Design and build scalable, cloud-native data pipelines (batch and streaming) supporting analytics, ML, and AI-powered applications

  
  


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  Architect enterprise-grade data models across data lakes, warehouses, and real-time systems (Snowflake, Databricks, Kafka, DBT)

  
  


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  Define standards for data governance, reliability, performance, and cost optimization

  
  


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  Optimize storage formats and distributed data systems (Parquet, Delta Lake, Iceberg)

  
  

AI & LLM-Enabled Systems

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  Develop Retrieval-Augmented Generation (RAG) systems integrating structured and unstructured enterprise data

  
  


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  Design and implement agentic workflows using frameworks such as LangChain, LangGraph, LlamaIndex, n8n, or similar

  
  


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  Integrate LLM APIs (OpenAI, Anthropic, or similar) into secure, production-ready applications

  
  


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  Implement guardrails, validation layers, monitoring, and evaluation frameworks to mitigate hallucination, prompt injection, and data security risks

  
  

Backend & API Development

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  Build secure backend APIs (Python/FastAPI) to expose AI-powered capabilities

  
  


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  Ensure observability, monitoring, and cost controls across AI and data services

  
  


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  Contribute to microservices architecture and distributed system design

  
  

Collaboration & Leadership

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  Partner cross-functionally with Product, Engineering, and Operations to translate business requirements into scalable technical solutions

  
  


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  Mentor junior engineers and contribute to architectural standards and best practices

  
  


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  Drive innovation in data engineering and AI-powered logistics systems

  
  

Qualifications

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  Bachelor’s degree in Computer Science or equivalent practical experience

  
  


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  8+ years of software or data engineering experience in production environments

  
  


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  Strong expertise in data modeling, distributed systems, and scalable cloud architectures

  
  


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  Hands-on experience with ETL/ELT frameworks and streaming technologies (Kafka, Spark, HEVO, Snowflake, DBT, etc.)

  
  


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  Advanced SQL skills and deep understanding of modern storage formats

  
  


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  Proficiency in Python and RESTful API development

  
  


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  Experience integrating LLM APIs into production applications

  
  


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  Strong understanding of system reliability, observability, and cost management in cloud environments

  
  

Desired Experience

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  Experience building RAG pipelines including embeddings, vector search, chunking strategies, and hybrid retrieval

  
  


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  Experience designing multi-agent or agentic AI workflows with orchestration frameworks

  
  


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  Knowledge of LLM evaluation, monitoring, and tracing tools (LangSmith or similar)

  
  


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  Experience with microservices architecture and distributed system design

  
  


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  Exposure to transportation, logistics, or supply chain domains

  
  


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  Active GitHub contributions or demonstrated passion for emerging AI and data technologies

  
  

Why Join Cargomatic?

We offer competitive compensation and a comprehensive benefits package, including:

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  Medical, Dental, and Vision insurance

  
  


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  401(k) with company match

  
  


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  Flexible Spending Accounts (FSA)

  
  


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  Company-paid Life and Disability insurance

  
  


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  Flexible Paid Time Off (PTO) and company holidays

  
  


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  Paid Parental Leave

  
  


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  Employee Assistance Program (EAP)

  
  


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  Opportunity to build cutting-edge AI solutions in a high-growth logistics technology company

  
  


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  Collaborative, high-impact team environment

  
  

Cargomatic is proud to be an Equal Opportunity Employer. We are committed to creating a diverse and inclusive workplace where all employees feel valued and empowered to succeed.