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Snowflake Intern Jobs in Connecticut (NOW HIRING)

The Hartford

Director of Data Science

Hartford, CT · On-site +1

$153K - $229K/yr

Support hiring and onboarding, including intern and actuarial student rotations. Strategic ... Experience in SQL and familiarity with cloud-native environments (e.g., Snowflake, Sagemaker). Able ...

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Snowflake Intern information

See Connecticut salary details

$8

$16

$23

How much do snowflake intern jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for snowflake intern in Connecticut is $16.21, according to ZipRecruiter salary data. Most workers in this role earn between $13.70 and $18.32 per hour, depending on experience, location, and employer.

What types of projects can a Snowflake intern expect to work on, and how do these projects support professional development?

As a Snowflake Intern, you can expect to work on a variety of projects such as developing data pipelines, optimizing SQL queries, supporting data migration efforts, and assisting with cloud data warehouse integrations. These projects are typically designed to provide hands-on experience with Snowflake's platform and related cloud technologies, allowing interns to build practical technical skills. You'll often collaborate with experienced engineers and data analysts, gaining insight into real-world data engineering workflows and best practices. This exposure not only enhances your technical toolkit but also helps you understand the collaborative dynamics of data teams, positioning you well for future roles in data engineering or analytics.

What are the key skills and qualifications needed to thrive as a Snowflake intern, and why are they important?

To thrive as a Snowflake Intern, you should have a solid understanding of SQL, data warehousing concepts, and programming languages such as Python or Java, often supported by ongoing coursework in computer science or a related field. Familiarity with the Snowflake platform, cloud services like AWS or Azure, and data analytics tools is highly beneficial. Strong problem-solving, attention to detail, and effective communication skills help you collaborate and learn quickly in a team environment. These competencies are vital to contribute meaningfully to projects and adapt to the fast-paced, data-driven work at Snowflake.

What is the difference between Snowflake Intern vs Snowflake Developer?

AspectSnowflake InternSnowflake Developer
Required CredentialsBasic understanding of cloud data platforms, possibly some coursework or certificationsProficiency in SQL, data warehousing, and Snowflake-specific features, often with relevant certifications
Work EnvironmentInternship setting, learning-focused, entry-level tasksFull-time role, development-focused, responsible for building and maintaining Snowflake data solutions
Employer & Industry UsageInternships in tech companies, data teams, or consulting firmsData engineering teams across various industries using Snowflake for data management

The main difference between a Snowflake Intern and a Snowflake Developer lies in experience, responsibilities, and skill level. Interns are typically in learning roles with entry-level tasks, while developers are responsible for designing and implementing Snowflake data solutions, requiring more expertise and certifications.

What does a Snowflake intern do?

A Snowflake Intern typically works on projects related to data warehousing, cloud computing, and software engineering using the Snowflake platform. Interns may assist with building data pipelines, optimizing queries, or developing new features under the guidance of experienced engineers. The internship provides hands-on experience with real-world data challenges and exposure to modern cloud technologies. Interns are encouraged to learn, collaborate, and contribute to the team’s goals while gaining insights into the industry.
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Snowflake Intern jobs near you

Data Engineering Internship (Summer 2027)

Castleton Commodities International, LLC

Stamford, CT • On-site

$122K - $146K/yr

Full-time

Posted 17 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.

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