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Data Engineering Internship Jobs in Baton Rouge, LA

Danaher

Digital Analyst Internships

Baton Rouge, LA

$94K - $111K/yr

By submitting your interest, you'll be among the first to know when internship opportunities open ... About Digital Analyst Roles at Danaher Are you passionate about data, customer experience, and ...

BREC, LA

Natural Resource Specialist

Baton Rouge, LA · On-site

$16.82 - $26.91/hr

Planning and Engineering Opening Date: 05/22/2026 Closing Date: Continuous FLSA: Non-Exempt General ... volunteer, internship, or work experience Combination of experience and/or education may be ...

All JobsData Engineering Internship JobsData Engineering Internship Jobs in Baton Rouge, LA

Data Engineering Internship information

See Baton Rouge, LA salary details

$10

$18

$28

How much do data engineering internship jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for data engineering internship in Baton Rouge, LA is $18.55, according to ZipRecruiter salary data. Most workers in this role earn between $15.48 and $20.10 per hour, depending on experience, location, and employer.

What types of projects or tasks can I expect to work on during a Data Engineering Internship?

As a Data Engineering Intern, you can expect to work on a variety of tasks such as building data pipelines, cleaning and transforming raw data, and assisting in the integration of data from multiple sources. You may also support the team in optimizing database performance and ensuring data quality. Interns often collaborate with data scientists, analysts, and software engineers, gaining exposure to different tools and technologies like SQL, Python, and cloud platforms. These experiences provide a strong foundation for a future career in data engineering.

What are the key skills and qualifications needed to thrive as a Data Engineering Intern, and why are they important?

To thrive as a Data Engineering Intern, you need a solid grasp of programming (especially Python or Java), databases (SQL/NoSQL), and data structures, often demonstrated by coursework or relevant projects. Familiarity with data processing tools like Apache Spark, ETL pipelines, and cloud platforms such as AWS or Google Cloud is highly beneficial. Strong problem-solving abilities, attention to detail, and effective communication help interns excel in collaborative and fast-paced environments. These skills are crucial for building reliable data pipelines and supporting data-driven decision-making within organizations.

Do CS interns get paid?

Data engineering internships typically offer paid positions, with compensation varying by company, location, and internship duration. Many internships also provide valuable experience working with tools like SQL, Python, and cloud platforms. However, some unpaid internships exist, so it is important to verify the specific internship's compensation details before applying.

What is the difference between Data Engineering Internship vs Data Analyst Internship?

AspectData Engineering InternshipData Analyst Internship
Required SkillsSQL, Python, ETL, cloud platformsExcel, SQL, data visualization tools
Work EnvironmentData pipelines, backend systems, cloud infrastructureData reporting, dashboards, business insights
Industry UsageTech, finance, healthcare, e-commerceRetail, marketing, finance, consulting

Data Engineering Internships focus on building and maintaining data pipelines and infrastructure, requiring technical skills like SQL and Python. Data Analyst Internships emphasize analyzing data to generate insights, often using Excel and visualization tools. Both roles are common in tech-driven industries but serve different functions within data teams.

Will AI replace data engineer?

AI is unlikely to fully replace data engineers, as their role involves designing, building, and maintaining data pipelines and infrastructure that require human expertise. Instead, AI tools can automate routine tasks, allowing data engineers to focus on complex problem-solving, system architecture, and ensuring data quality. Skills in programming, cloud platforms, and data management remain essential for the role.

How hard is it to get an internship in data science?

Securing a data engineering internship can be competitive, often requiring a strong foundation in programming languages like Python or SQL, understanding of data pipelines, and relevant coursework or projects. Candidates with prior experience, certifications, or familiarity with tools such as Apache Spark or cloud platforms tend to have better chances. Demonstrating problem-solving skills and a willingness to learn are also important factors in the application process.

What is a data engineering internship?

A data engineering internship is a temporary position where interns assist in designing, building, and maintaining data pipelines and infrastructure. It typically involves working with tools like SQL, Python, and cloud platforms, and provides hands-on experience in managing large datasets and supporting data-driven projects.
What are popular job titles related to Data Engineering Internship jobs in Baton Rouge, LA? For Data Engineering Internship jobs in Baton Rouge, LA, the most frequently searched job titles are:
What job categories do people searching Data Engineering Internship jobs in Baton Rouge, LA look for? The top searched job categories for Data Engineering Internship jobs in Baton Rouge, LA are:
Data Engineering Internship jobs near you
Associate Data Engineer - Client Innovation Center (Entry Level)

Associate Data Engineer - Client Innovation Center (Entry Level)

IBM

Baton Rouge, LA • On-site

$15.25 - $20/hr

Full-time

Posted 2 days ago

IBM rating

7.9

Company rating: 7.9 out of 10

Based on 72 frontline employees who took The Breakroom Quiz

99th of 188 rated software companies

Job description

Job Summary:
IBM Consulting Client Innovation Centers (CICs) are environments where technologists build real solutions for clients. The Associate Data Engineer role is entry-level, focusing on supporting the development and maintenance of data pipelines and platforms while collaborating with experienced practitioners.
Responsibilities:
• Support the development and maintenance of data pipelines used for analytics, reporting, and machine learning
• Assist with extracting, transforming, and loading (ETL/ELT) data from multiple sources into data platforms
• Contribute to data cleansing, validation, and transformation activities using Python and SQL
• Help prepare datasets for downstream consumption by analytics and data science teams
• Support batch and, where applicable, near-real-time data processing workflows under guidance
• Collaborate with data engineers, data scientists, and other team members in Agile delivery environments
• Build data engineering skills through training, mentorship, and hands-on delivery experience
• Work with functional and technical team members to help integrate data solutions into client business environments
Qualifications:
Required:
• Strong foundation in computer science fundamentals, including data structures and algorithms
• Strong analytical and problem-solving skills with attention to data quality and reliability
• Comfortable working onsite in a collaborative, team-based environment
• Ability to work effectively in a technology-driven consulting environment where tools, platforms, and client needs evolve over time
• Strong analytical and problem-solving skills, with the ability to approach complex tasks using structured, logical thinking
• Ability to learn new systems and technologies quickly and apply them in a delivery setting
• Proficiency in Python (preferred) or another programming language used for data processing
• Hands-on experience using data manipulation tools such as pandas, NumPy, and SQL, gained through coursework, labs, projects, or internships
• Ability to write clear, maintainable code for data transformation and processing tasks
• Understanding of ETL/ELT concepts and how data moves from source systems to consumption layers
• Familiarity with relational databases and SQL for querying and data manipulation
• Basic understanding of data modeling concepts such as schemas, normalization, or dimensional models
• Exposure to cloud-based data or analytics platforms (e.g., AWS, Azure, or Google Cloud) through coursework, labs, or projects
• Familiarity with core cloud data services such as object storage, databases, or analytics services
• Ability to translate business or functional requirements into technical solutions, with guidance from senior team members
• Comfortable working onsite in a collaborative, team-based environment
• Strong willingness to learn, accept feedback, and continuously improve
• Familiarity with generative AI concepts, including basic modeling approaches, responsible use, and ethical considerations, gained through coursework, projects, or self-study
Preferred:
• Master's Degree
• Exposure to distributed data processing tools such as Apache Spark or PySpark
• Familiarity with modern data warehouse technologies (e.g., Snowflake, Redshift, BigQuery)
• Exposure to streaming or event-based data concepts
• Familiarity with version control tools such as Git
• Basic awareness of how data engineering supports machine learning workflows
Company:
IBM provides technology and consulting, including software, infrastructure systems, and cloud-based solutions. Founded in 1911, the company is headquartered in Armonk, USA, with a team of 10001+ employees. The company is currently Late Stage.

What IBM employees say

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Benefits

Hours and flexibility

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About IBM

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At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Armonk, NY, US

Year founded

1911

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