Engineering Intern – Transport Analytics

Job description

Job Description: Role Summary & Core Objective The Transport Analytics team serves as the backbone data warehouse ecosystem powering our suite of inland transport products. We bridge complex supply chain logistics with high-performance data systems to solve real-world operational challenges. We are seeking a high-octane Engineering Intern who combines strong core software engineering fundamentals with a curiosity for modern AI paradigms to drive quantifiable business outcomes: revenue growth, cost reduction, or elevated customer satisfaction. Key Responsibilities Full-Stack & API Development: Design, build, and maintain lightweight web applications and RESTful APIs that interface directly with our analytics database ecosystem. Data & Analytics Integration: Query, transform, and leverage data warehouse pipelines to feed user-facing analytical tools and internal operational dashboards. AI & Agentic Experimentation: Assist in prototyping modern AI workflows—exploring Agentic AI frameworks, LLM integrations, and intelligent automation to solve transport analytics challenges. Cross-Functional Problem Solving: Work closely with product managers and business stakeholders to translate complex business problems into reliable, efficient engineering solutions. Rapid Prototyping: Adapt quickly to changing product needs, delivering functional proof-of-concepts (PoCs) that can be validated directly with end-users. Qualifications & Skill Requirements Minimum Qualifications Education: Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or a related technical discipline. Polyglot Programming: Solid foundational knowledge and hands-on project experience in both Python and Java. Database & Web Fundamentals: Practical understanding of relational database systems (SQL/NoSQL) and experience building web applications connected via backend DB APIs. Modern AI Awareness: Familiarity with Generative AI concepts, LLM application architectures, or emerging Agentic AI frameworks (e.g., LangChain, AutoGen, CrewAI, or tool-use patterns). Problem-Solving Mindset: A structured, analytical approach to troubleshooting and breaking down ambiguous business problems into clear technical components. Preferred Qualifications Logistics & Data Pipelines: Prior internship, open-source contribution, or academic project experience involving data warehousing, ETL pipelines. Cloud & DevOps Tools: Basic understanding of cloud infrastructure (AWS /Azure) and containerization tools like Docker. Communication Skills: Excellent verbal and written communication skills with the ability to articulate technical concepts to non-technical business partners. What Success Looks Like (KPIs & Impact) During your internship, success will be measured by your ability to deliver end-to-end engineering solutions that drive tangible output across at least one of these core business pillars: Cost Reduction: Automating inefficient manual workflows or optimizing query performance to cut cloud infrastructure and operational overhead. Revenue Growth: Building feature prototypes or analytics tools that unlock new customer capabilities or identify upsell opportunities across transport products. Customer Satisfaction (CSAT): Resolving latency bottlenecks and improving data visibility for transport stakeholders to deliver a seamless user experience. Why Join Us? High Ownership & Impact: Work on live data infrastructure and customer-impacting products rather than isolated side projects. Mentorship & Growth: Collaborate directly with senior data engineers, software architects, and technical product managers who are invested in your career. Cutting-Edge Tech Stack: Get hands-on exposure at the intersection of enterprise data warehouses, full-stack web development, and next-gen AI frameworks. Kaleris is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.