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Data Engineer Internship Jobs in Austin, TX (NOW HIRING)

SpaceX

Data Engineer (Starlink)

Bastrop, TX · On-site

$113K - $136K/yr

Bachelor's degree in computer science, data science, physics, mathematics, or another STEM discipline * 1+ years of professional data engineering or software engineering experience (internship ...

SpaceX

Data Engineer (Starlink)

Bastrop, TX · On-site

$113K - $136K/yr

... internship experience applicable) • 1+ years of development experience in Python or another modern programming language (SQL, etc.) Preferred : • Experience improving CRM data quality (deduping ...

SpaceX

Data Engineer (Starlink)

Bastrop, TX · On-site

$113K - $136K/yr

Bachelor's degree in computer science, data science, physics, mathematics, or another STEM discipline * 1+ years of professional data engineering or software engineering experience (internship ...

SpaceX

Data Engineer (Starlink)

Bastrop, TX · On-site

$113K - $136K/yr

Bachelor's degree in computer science, data science, physics, mathematics, or another STEM discipline * 1+ years of professional data engineering or software engineering experience (internship ...

Cypress HCM

Data Science Engineer

Austin, TX · Hybrid

$65 - $69.72/hr

Data Science Engineer Job Details * Data Science Engineer (Contract) * Location: Austin TX, 78758 ... This role is not suitable for entry-level candidates or interns. Compensation: * $65.00 to $69.72 ...

ANS

Senior Electrical Engineer

Austin, TX · On-site

$139K - $170K/yr

We're allergic to bureaucracy, thrive on innovation, and embrace data-driven decisions. If you love ... Internship or project experience in power systems or renewables * Involvement in student ...

Apple

Data Center, Product Design Engineer

Austin, TX · On-site

$127K - $153K/yr

The Apple Data Center Product Design Engineering team works with other engineering groups to ... equivalent internship experience Experience with the server mechanical development cycle from ...

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Data Engineer Internship information

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How much do data engineer internship jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for data engineer internship in Austin, TX is $25.19, according to ZipRecruiter salary data. Most workers in this role earn between $20.48 and $28.61 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in a data engineer internship, and why are they important?

To thrive as a Data Engineer Intern, you need a solid background in programming (especially Python or Java), SQL, and basic data management concepts, often gained through coursework in computer science, data science, or related fields. Experience with tools like SQL databases, ETL pipelines, and cloud platforms (such as AWS or Azure), as well as familiarity with big data frameworks like Hadoop or Spark, is highly valuable. Strong analytical thinking, attention to detail, and the ability to communicate technical information clearly help interns collaborate effectively within diverse teams. These skills are vital for supporting data infrastructure development, ensuring data quality, and contributing to impactful data-driven solutions.

What is a data engineer internship?

A Data Engineer Internship is a temporary, entry-level role where interns gain hands-on experience in data infrastructure, ETL pipelines, and database management. Interns typically work with large datasets, assist in building data models, and collaborate with data scientists and analysts to ensure efficient data processing. They learn tools like SQL, Python, and cloud platforms while improving data quality and automation processes. This role provides valuable industry experience and prepares interns for full-time data engineering positions.

What types of projects or tasks can I expect to work on during a data engineer internship?

As a Data Engineer Intern, you can expect to assist with building and maintaining data pipelines, cleaning and transforming datasets, and supporting the integration of new data sources. You may also help optimize database performance, troubleshoot data quality issues, and collaborate with data scientists or analysts to ensure data accessibility. Interns often work on real-world projects that offer hands-on experience with tools and technologies common in the industry. This exposure not only builds your technical skills but also provides valuable insights into how data engineering supports business decision-making and analytics.

What are the most commonly searched types of Data Engineer jobs in Austin, TX? The most popular types of Data Engineer jobs in Austin, TX are:
What are popular job titles related to Data Engineer Internship jobs in Austin, TX? For Data Engineer Internship jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Data Engineer Internship jobs in Austin, TX look for? The top searched job categories for Data Engineer Internship jobs in Austin, TX are:
What cities near Austin, TX are hiring for Data Engineer Internship jobs? Cities near Austin, TX with the most Data Engineer Internship job openings:
Data Engineer Internship jobs near you
Infographic showing various Data Engineer Internship job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $52,402 per year, or $25.2 per hour.

Data Engineer

Texas State Library and Archives Commision

Austin, TX • On-site

$113K - $136K/yr

Full-time

Re-posted 20 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.

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