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Systems Engineering Internships Jobs in New York

Supervise a team of Junior System Engineers and Interns * Act as an escalation point to your team for technical and non-technical issues * Approve PTO and time entry management for your team.

Our interns are embedded into small, collaborative engineering teams across the company. You'll work closely with your mentor and teammates to ship meaningful features, tools, or systems. Whether you ...

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Systems Engineering Internships information

See New York salary details

$58.5K

$139.2K

$182.7K

How much do systems engineering internships jobs pay per year?

As of Aug 27, 2026, the average yearly pay for systems engineering internships in New York is $139,177.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,200.00 and $171,800.00 per year, depending on experience, location, and employer.

What is a systems engineering internship?

Systems Engineering Internships are short-term, hands-on training opportunities for students or recent graduates interested in systems engineering. Interns work alongside experienced engineers to help design, analyze, and improve complex systems in industries such as aerospace, technology, or manufacturing. These internships typically involve tasks like requirements analysis, modeling, testing, and documentation. The goal is to provide practical experience and a deeper understanding of the systems engineering process, often serving as a stepping stone to a full-time engineering role.

What are the key skills and qualifications needed to thrive as a systems engineering intern?

To thrive as a Systems Engineering Intern, you generally need a background in engineering or computer science, strong analytical thinking, and a solid grasp of systems theory. Familiarity with tools such as MATLAB, Simulink, or requirements management software, and coursework or certifications in systems engineering principles are often expected. Strong soft skills include effective communication, teamwork, and a willingness to learn in a collaborative environment. These skills and qualities are essential for contributing to complex projects, adapting to new technologies, and supporting the broader engineering team.

What types of projects do systems engineering interns typically work on?

Systems Engineering Interns often participate in multidisciplinary projects such as system integration, requirements analysis, and testing of hardware or software systems. These projects provide hands-on experience with real-world engineering challenges and exposure to tools like MATLAB, Simulink, or various modeling software. Interns usually collaborate closely with senior engineers and cross-functional teams, fostering both technical and teamwork skills. This experience not only strengthens their engineering foundation but also helps them build a professional network and gain insights into potential career paths within systems engineering.

What is the difference between Systems Engineering Internships vs Mechanical Engineering Internships?

AspectSystems Engineering InternshipsMechanical Engineering Internships
Required CredentialsTypically pursuing or holding a degree in systems engineering, electrical engineering, or related fieldsUsually pursuing or holding a degree in mechanical engineering or related disciplines
Work EnvironmentInvolves systems design, integration, and analysis often in aerospace, defense, or tech industriesFocuses on product design, manufacturing, and testing in automotive, aerospace, or manufacturing sectors
Employer & Industry UsageCommonly used in industries requiring complex system integration like aerospace, defense, and tech companiesPrevalent in manufacturing, automotive, and aerospace industries

Systems Engineering Internships and Mechanical Engineering Internships share some foundational engineering principles but differ in focus areas. Systems internships emphasize system integration and analysis, while mechanical internships concentrate on product design and manufacturing. Both roles are valuable entry points in engineering careers, often requiring related technical degrees and offering industry-specific experiences.

What cities in New York are hiring for Systems Engineering Internships jobs?

Cities in New York with the most Systems Engineering Internships job openings:

Infographic showing various Systems Engineering Internships job openings in New York as of August 2026, with employment types broken down into 84% Full Time, 11% Part Time, 4% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $139,177 per year, or $66.9 per hour.

Data Engineering Internship (Summer 2027)

Stamford, CT โ€ข On-site

Castleton Commodities International, LLC
Oil and Gas Extractionย โ€ขย 501 - 1,000 employees

$122K - $146K/yr

Full-time

Re-posted 7 days ago


Job description

Application Deadline: September 1, 11:59 pm EST
Program Summary - Data Science & Technology Internship
Company Overview:
Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets. Our strategically integrated platform has generated strong risk-adjusted returns for our investors since our formation.
Position Overview:
CCI is developing a leading-edge Data Science platform, as staying at the forefront of data management and analytics is essential to our investment strategy. We are looking for motivated and detail-oriented Data Engineering Interns to join our Global Data Science & Technology team in Houston, TX, Stamford, CT, & New York City offices. The Data Engineering Intern will work closely with our Data Science, Data Engineering and Commercial teams to build and optimize data pipelines that power our analytics, forecasting, and investment decision-making processes. This is a hands-on technical internship ideal for someone who enjoys solving real-world data challenges, especially around ingesting, scraping, and managing large datasets across the commodity markets.
Responsibilities:
  • Develop and maintain robust data ingestion pipelines from various internal and external sources, including APIs, FTP endpoints, and cloud data providers.
  • Develop data ingestion and transformation pipelines using Python and SQL, publishing Snowflake for downstream use in analytics and forecasting tools.
  • Work on data architecture and data management projects for both new and existing data sources.
  • Design and implement ETL processes to clean, normalize, and store structured and semi-structured data in Snowflake, our core relational data warehouse.
  • Analyze data pipeline performance and implement optimizations to improve efficiency and reliability.
  • Conduct data quality checks and build validation logic to identify anomalies and ensure data integrity for use by commercial trading and analytics teams.
  • Automate data workflows using Python, SQL, and orchestration tools (e.g., Airflow or similar).
  • Assist in transitioning legacy datasets and codebases into scalable, cloud-native workflows aligned with our modern data architecture.
  • Document data sources, pipeline logic, and data models to ensure maintainability and knowledge transfer.

Qualifications:
  • Currently pursuing a Bachelor's or higher degree in Computer Science, Engineering, Management Information Systems, or related technical field.
  • Expected graduation date of Winter 2027 or Spring/Summer 2028.
  • Strong programming experience in Python (preferred libraries: pandas, NumPy, SQL alchemy, etc.).
  • Strong understanding of SQL and experience querying relational databases (Snowflake a plus).
  • Exposure to or interest in cloud platforms (e.g., AWS, Azure), particularly with cloud data storage and compute.
  • Familiarity with web scraping frameworks and handling large-scale structured and unstructured data sources.