Senior Data Engineer for Scalable Analytics Infrastructure

Our company is seeking a Senior Full Stack SDE with Data Engineering expertise to build cutting-edge software and data infrastructure for AI-driven Trucking Science-as-a-Service platform.

The role involves designing and building full stack applications using Python, Streamlit, and modern web frameworks to power internal tools, analytics dashboards, and customer-facing products.

We are looking for someone who can develop scalable data pipelines, implement low-latency backend services, integrate front-end components with backend systems, collaborate with data scientists / ML engineers, define and evolve data strategy / architecture, implement DevOps best practices, ensure data integrity / privacy, and contribute to product planning / roadmaps.

Required qualifications include 5+ years of professional software development experience, hands-on experience with modern front-end technologies, experience designing / managing scalable data pipelines, defining data architecture / engineering architecture, building / maintaining well-structured APIs / microservices in a cloud environment, working knowledge / data validation / privacy / governance, and strong communication / collaboration skills.

Desirable experience includes technology experience with Snowflake, Streamlit, Folium, Plotly, AG Grid, Kubernetes, JavaScript / CSS, Flask / Fast API / SQLAlchemy, exposure to machine learning workflows / collaboration with data scientists / MLOps teams, experience building / scaling analytics tools / business intelligence systems / SaaS data products, familiarity with geospatial data / visualization libraries, knowledge of CI / CD tools / modern DevOps practices, contributions to early-stage product development / high-growth startups, passion for transportation / logistics / applying technology to operational systems.

Why join us? We offer massive market opportunity, real business impact, builder's culture, tight feedback loop, tech stack you'll love, and mission-driven team.