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Airflow Internship Jobs (NOW HIRING)

Bedgear

FUTURE OPPORTUNITIES

Farmingdale, NY · On-site

At BEDGEAR, we design high-performance sleep essentials engineered for airflow, recovery, and ... Internships Minimum Requirements: - Must be 18 years of age or older - HS Diploma or GED - Must be ...

Archer

Staff Data Engineer

San Jose, CA

$17K - $215K/yr

What You Need: * 5+ years of professional data engineering experience excluding internships. * BS ... Airflow/Prefect/Dagster Bonus Qualifications: * Experience with CDC (Change Data Capture ...

Jobtailor

Data Engineer

Austin, TX · On-site

$90 - $130/hr

Financial industry internships / experience are a plus. * Experience with Java recommended. * Experience with on‑premises data infrastructure (e.g., Hadoop) * Experience with Apache Airflow or ...

Roku

Senior Data Scientist

New York, NY · On-site +1

$126K - $199K/yr

Build data processing and reporting pipelines using SQL, Python, and Airflow. * Develop data ... Must have prior experience, internship, project background, or advance level coursework in each of ...

Bedgear

FUTURE OPPORTUNITIES

Farmingdale, NY · On-site

At BEDGEAR, we design high-performance sleep essentials engineered for airflow, recovery, and ... Internships Minimum Requirements: - Must be 18 years of age or older - HS Diploma or GED - Must be ...

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Airflow Internship information

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How much do airflow internship jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for airflow internship in the United States is $17.31, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What is an Airflow internship?

An Airflow internship is a temporary position, often for students or recent graduates, that provides hands-on experience working with Apache Airflow, an open-source platform used to programmatically author, schedule, and monitor data workflows. Interns typically assist with building, managing, and optimizing data pipelines, learning how to orchestrate complex data processes in real-world environments. The internship helps develop technical skills in Python, workflow management, and cloud services, preparing individuals for data engineering or related roles. It is usually offered by companies with significant data processing needs, such as tech firms, financial institutions, or consulting companies.

What types of projects do Airflow interns typically work on, and how does this experience contribute to their professional development?

Airflow interns often work on real-world data pipeline projects, such as automating data extraction, transformation, and loading (ETL) processes or optimizing workflow scheduling for business analytics. These projects provide hands-on experience with Apache Airflow, Python programming, and cloud-based data tools, allowing interns to build practical skills in data engineering. Collaboration is common, as interns usually work alongside data engineers and analysts, gaining insight into team-based problem-solving and best practices. This experience not only strengthens technical expertise but also prepares interns for future roles in data engineering or DevOps.

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

To thrive as an Airflow Intern, you generally need a foundational understanding of Python programming, data engineering concepts, and familiarity with workflow orchestration principles. Experience or coursework with Apache Airflow, SQL, and cloud platforms like AWS or GCP is often expected, along with version control tools such as Git. Strong problem-solving skills, curiosity, and effective communication help interns collaborate and quickly learn in dynamic technical environments. These competencies are crucial for efficiently automating data pipelines and supporting the seamless flow of information within data-driven teams.

What is the difference between Airflow Internship vs Data Engineer Internship?

AspectAirflow InternshipData Engineer Internship
Required SkillsKnowledge of Apache Airflow, Python, ETL workflowsProgramming (Python, SQL), data modeling, ETL pipelines
Work EnvironmentData teams, cloud platforms, automation projectsData infrastructure, database management, big data tools
Industry UsageData pipeline automation, workflow orchestrationData storage, processing, and analysis

Both internships involve working with data technologies, but an Airflow Internship focuses specifically on workflow orchestration using Apache Airflow, while a Data Engineer Internship covers broader data infrastructure and pipeline development. Candidates should have some programming and data skills, with the choice depending on their interest in automation versus data architecture.

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Airflow Internship jobs near you
Infographic showing various Airflow Internship job openings in the United States as of August 2026, with employment types broken down into 15% Internship, 54% Full Time, and 31% Part Time. Highlights an 84% In-person, 8% Hybrid, and 8% Remote job distribution, with an average salary of $35,995 per year, or $17.3 per hour.

Data Engineer

Texas State Library and Archives Commision

Austin, TX • On-site

$113K - $136K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

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.

Apply