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Internship Dagster Jobs (NOW HIRING)

Data Engineer I

San Francisco, CA · On-site

$115K - $145K/yr

Internship, co-op, or open-source experience writing data pipelines in production-like environments ... Exposure to data pipeline scheduling and orchestration tools, such as Apache Airflow, Dagster, Argo ...

Data Engineer

Salt Lake City, UT · On-site

$110K - $133K/yr

... internship (we care about proof you can ship and debug). • Solid engineering habits: Git ... Dagster, Prefect, or similar). • Experience with a cloud data warehouse (Snowflake, BigQuery ...

Data Engineer I

San Francisco, CA · On-site

$115K - $145K/yr

Internship, co-op, or open-source experience writing data pipelines in production-like environments ... Exposure to data pipeline scheduling and orchestration tools, such as Apache Airflow, Dagster, Argo ...

Sr. Software Engineer

Tampa, FL · On-site

$115K - $152K/yr

Mentor junior engineers and interns, fostering a collaborative environment and promoting ... Dagster, along with Linux/Unix operating systems. * Experience designing database architectures ...

Sr. Software Engineer

Tampa, FL · On-site

$115K - $152K/yr

Mentor junior engineers and interns, fostering a collaborative environment and promoting ... Dagster, along with Linux/Unix operating systems. * Experience designing database architectures ...

Data Engineer

Salt Lake City, UT · On-site

$105K - $126K/yr

Some hands-on exposure to ETL/ELT or pipelines in production or in a substantial project/internship ... Orchestration experience (Airflow, Dagster, Prefect, or similar). * Experience with a cloud data ...

Internship Dagster information

See salary details

$8

$15

$21

How much do internship dagster jobs pay per hour?

As of Jun 13, 2026, the average hourly pay for internship dagster in the United States is $15.54, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $17.55 per hour, depending on experience, location, and employer.

What is the difference between Internship Dagster vs Data Engineer Intern?

AspectInternship DagsterData Engineer Intern
Required CredentialsBasic programming, understanding of data pipelinesProgramming skills, some knowledge of data architecture
Work EnvironmentCollaborative, project-based, tech-focusedTeam-oriented, data-centric, fast-paced
Employer & Industry UsageTech companies, startups, data-focused organizationsTech firms, finance, healthcare, any data-driven industry

Internship Dagster typically involves learning data pipeline orchestration using Dagster, focusing on workflow management. Data Engineer Internships are broader, covering data architecture, pipeline development, and database management. Both roles are entry-level, require programming skills, and are common in tech and data industries, but Internship Dagster is more specialized in workflow orchestration tools.

More about Internship Dagster jobs
What cities are hiring for Internship Dagster jobs? Cities with the most Internship Dagster job openings:
What are the most commonly searched types of Dagster jobs? The most popular types of Dagster jobs are:
What states have the most Internship Dagster jobs? States with the most job openings for Internship Dagster jobs include:
Infographic showing various Internship Dagster job openings in the United States as of June 2026, with employment types broken down into 15% Internship, 7% As Needed, 74% Part Time, and 4% Temporary. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $32,333 per year, or $15.5 per hour.

$113K - $136K/yr

Full-time

Posted 24 days ago


Job description

We're looking for a Data Engineer to help build and maintain the data pipelines that power our investment, research, and analytics teams. You'll work closely with data scientists, quants, and investors to onboard new datasets, ensure data quality, and maintain the reliability of the data that drives decision-making across the firm.
What You'll Do
• Build, maintain, and troubleshoot ETL pipelines (Airflow, Dagster, or similar).
• Ingest and deeply understand new datasets - their structure, quirks, and business meaning.
• Maintain high-quality, well-documented datasets used across the organization.
• Partner with non-engineering stakeholders to understand data needs and guide them to the right sources.
• Evaluate data vendors and ensure we use the best data for each use case.
What We're Looking For
• Strong Python and SQL skills.
• Experience building data pipelines; familiarity with Spark or Pandas a plus.
• Strong attention to detail and persistence in debugging data issues.
• Clear communication skills, especially with non-technical audiences.
• 1-3 years of experience (or strong internships); senior candidates also welcome.
Who Thrives Here
• Curious, detail-oriented engineers who like diving deep into complex datasets.
• People who enjoy owning problems end-to-end and defining their own requirements.
• Engineers who build reliable, maintainable systems and prefer fast, iterative execution.
Why Join
• High-impact role: the data you manage powers investment decisions across the firm.
• Broad exposure to many types of financial and alternative data.
• Opportunity to shape a growing data function and work with teams across the entire company.
Qualifications
• Strong Python and SQL skills.
• Experience building data pipelines; familiarity with Spark or Pandas a plus.
• Strong attention to detail and persistence in debugging data issues.
• Clear communication skills, especially with non-technical audiences.
• 1-3 years of experience (or strong internships); senior candidates also welcome.
Why is This a Great Opportunity
You are building data infrastructure that directly drives investment decisions. The pipelines you own power research, analytics, and live decision making across the firm. This is not abstract data work. It affects capital allocation.
You work directly with quants, data scientists, and investors. You are not buried behind layers of product or management. You see how data is used, where it breaks, and how to make it better. That feedback loop is fast and real.
You get broad exposure to high value datasets. Market data, alternative data, vendor feeds, internal research outputs. You learn how data actually behaves in production, not how it looks in a demo.