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Weekend Data Engineer Internship Jobs in Austin, TX

SpaceX

Data Engineer (Starlink)

Bastrop, TX

$113K - $136K/yr

... software engineering experience (internship experience applicable) * 1+ years of development ... Must be available to work extended hours and weekends as needed * Willingness to travel to customer ...

SpaceX

Data Engineer (Starlink)

Bastrop, TX · On-site

$113K - $136K/yr

... internship experience applicable) * 1+ years of development experience in Python or another modern ... Must be available to work extended hours and weekends as needed * Willingness to travel to customer ...

SpaceX

Data Engineer (Starlink)

Bastrop, TX · On-site

$113K - $136K/yr

... internship experience applicable) * 1+ years of development experience in Python or another modern ... Must be available to work extended hours and weekends as needed * Willingness to travel to customer ...

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 ...

K&L Gates

Senior Data Engineer

Austin, TX · On-site

$105K - $142K/yr

The Senior Data Engineer contributes to the Enterprise Applications, Data, and AI Platforms group ... weekends, with advance notice and flexible scheduling. • Demonstrate the ability to implement ...

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 ...

Apple

Applied Data Solutions Program (Internships)

Austin, TX · On-site

$113K - $136K/yr

Description To express interest in the Applied Data Solutions Program (ADSP) Internship, please ... engineering. Based on your interests and experiences you might be able to: • Work side-by-side ...

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All JobsData Engineer JobsWeekend Data Engineer Internship JobsWeekend Data Engineer Internship Jobs in Austin, TX

Weekend Data Engineer Internship information

See Austin, TX salary details

$44.1K

$128.6K

$175.9K

How much do weekend data engineer internship jobs pay per year?

As of Jul 30, 2026, the average yearly pay for weekend data engineer internship in Austin, TX is $128,576.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $136,300.00 per year, depending on experience, location, and employer.

What is the difference between Weekend Data Engineer Internship vs Weekend Data Analyst Internship?

AspectWeekend Data Engineer InternshipWeekend Data Analyst Internship
Required SkillsData pipeline development, SQL, Python, cloud platformsData visualization, SQL, Excel, basic analytics
Work EnvironmentTechnical teams, data engineering projectsBusiness teams, reporting and analysis tasks
Industry UsageTech, finance, e-commerceMarketing, retail, consulting

The Weekend Data Engineer Internship focuses on building and maintaining data pipelines and infrastructure, requiring technical skills like Python and cloud platforms. In contrast, the Weekend Data Analyst Internship emphasizes analyzing data and creating reports, with skills in visualization and Excel. Both roles are part-time, involve working with data teams, and are common in various industries, but they serve different functions within data management and analysis.

What are the most commonly searched types of Weekend Data Engineer jobs in Austin, TX? The most popular types of Weekend Data Engineer jobs in Austin, TX are:
Weekend Data Engineer Internship jobs near you

Data Engineer

Texas State Library and Archives Commision

Austin, TX • On-site

$113K - $136K/yr

Full-time

Re-posted 12 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.

Apply