Develop and maintain Python-based applications and automation workflows.
Build and enhance software pipelines that collect, process, and organize data from multiple sources.
Support and deploy solutions using cloud services such as AWS Lambda, InfluxDB, or equivalent GCP tools.
Analyze structured and unstructured data, including timeseries and network telemetry data, to identify key patterns.
Contribute to creating and maintaining analytics components using Elasticsearch and Kibana or equivalent.
Collaborate with engineers using Git, CI/CD workflows.
Document technical processes, write reusable code, and implement best practices for system reliability.
Explore new technologies such as agentic AI frameworks (e.g., LangGraph) and LLM-based automation solutions.

Requirements

Currently enrolled in a college degree program in Computer Science, Computer Engineering, Software Engineering, or a related field.
Proficiency in Python for backend development, scripting, or automation.
Understanding of data pipeline and integration concepts — collecting, transforming, and preparing data for analytics.
Exposure to AWS cloud services (Lambda, InfluxDB) or corresponding GCP components.
Familiarity with version control systems such as Git.
Experience with analytics or data‑driven projects through coursework, internships, or research.
Strong foundation in data structures, algorithms, and API design.
Excellent problem-solving skills, attention to detail, and ability to work collaboratively.

Benefits

Exposure to real-world production systems
Mentorship opportunities
Hands-on experience at the intersection of software engineering, data analytics, and emerging AI frameworks

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Pythondata pipelinedata integrationanalyticsdata structuresalgorithmsAPI designautomation workflowssoftware pipelinescloud services

Soft Skills

problem-solvingattention to detailcollaboration