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Sql Python Internship Jobs in Lafayette, LA (NOW HIRING)

Python, Java, C+, or C. * Google BigQuery or SQL. * Power Bi or Tableau. (Candidates with at least ... Co-Op/Internship in Manufacturing, Supply Chain, or Distribution with experience applying basic ...

Python, Java, C+, or C. * Google BigQuery or SQL. * Power Bi or Tableau. (Candidates with at least ... Co-Op/Internship in Manufacturing, Supply Chain, or Distribution with experience applying basic ...

Sql Python Internship information

See Lafayette, LA salary details

$12

$55

$82

How much do sql python internship jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for sql python internship in Lafayette, LA is $55.98, according to ZipRecruiter salary data. Most workers in this role earn between $46.15 and $63.61 per hour, depending on experience, location, and employer.

What is a SQL Python internship?

A SQL Python Internship is a temporary training position designed for students or recent graduates who want hands-on experience working with SQL databases and Python programming. Interns typically assist with data analysis, database management, and automation tasks using SQL and Python. The role helps individuals develop technical skills, gain exposure to real-world projects, and prepare for a career in data science, analytics, or software development.

What are some common projects or tasks I might work on during a SQL Python internship?

As a SQL Python intern, you can expect to work on a variety of data-driven projects such as cleaning and analyzing datasets, building data pipelines, and creating reports or dashboards. Typical tasks may include writing SQL queries to extract or manipulate data from databases, developing Python scripts for automation, and collaborating with data analysts or engineers on ongoing projects. You'll likely participate in team meetings, contribute to code reviews, and receive mentorship to help you develop both technical and professional skills. This hands-on experience is valuable for building a foundation in data engineering or analytics roles.

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

To succeed as an SQL Python Intern, you should have a foundational understanding of database concepts, SQL querying, and Python programming, often supported by coursework or relevant certifications. Familiarity with database management systems like MySQL or PostgreSQL, and experience using tools such as Jupyter Notebooks or version control systems like Git, are typically expected. Strong analytical thinking, attention to detail, and effective communication skills help interns collaborate and solve problems efficiently. These skills enable interns to contribute to data-driven projects and support the technical needs of their team.

What is the difference between Sql Python Internship vs Data Analyst Internship?

AspectSql Python InternshipData Analyst Internship
Required SkillsSQL, Python, basic data manipulationSQL, Excel, data visualization
Work EnvironmentTech companies, startups, data teamsBusiness, finance, marketing sectors
Industry UsageData engineering, software developmentBusiness insights, reporting

Sql Python Internships focus on developing skills in SQL and Python for data extraction and manipulation, often within tech environments. Data Analyst Internships emphasize data visualization and reporting skills for business decision-making. While both roles involve data handling, Sql Python Internships are more technical and programming-oriented, whereas Data Analyst Internships focus on interpreting data for strategic insights.

Healthcare Data Analyst (On-Site in Lafayette, LA)

FMOLHS

Lafayette, LA • On-site

Full-time

Re-posted 3 days ago


Job description

This role will be located on-site in Lafayette, LA.

The Healthcare Data Analyst 2 plays a crucial role in analyzing and interpreting complex health data to help improve patient outcomes, operational efficiency, and overall healthcare delivery within our health system. The ideal candidate will have advanced analytical skills, a strong understanding of healthcare data, and the ability to work collaboratively with various stakeholders across the organization.

Education: Bachelor's degree in Health Informatics, Data Science, Statistics, Public Health, Business/Healthcare Administration or a related field.

Experience: Minimum of 3 years of experience in healthcare data analysis or a related field including internship.

Technical Skills: Proficiency in data analysis tools and software, such as SQL, SAS, R, Python, or Tableau. Strong understanding of electronic health records (EHR) systems, healthcare databases, and data standards (e.g., ICD-10, CPT codes).

Analytical Skills: Advanced analytical and problem-solving skills. Ability to interpret complex data sets and provide meaningful insights.

Communication Skills: Excellent verbal and written communication skills. Ability to present data findings clearly and concisely to non-technical stakeholders.

Attention to Detail: Strong attention to detail and commitment to data accuracy and quality.

Team Player: Ability to work effectively in a collaborative, team-oriented environment.

Data Analysis and Reporting: Perform advanced data analysis to support clinical and operational decision-making. Generate comprehensive reports and data visualizations to communicate findings effectively.

Data Management: Ensure the accuracy, integrity, and security of healthcare data. Manage data extraction, transformation, and loading (ETL) processes.

Performance Metrics: Develop and monitor key performance indicators (KPIs) to assess the effectiveness of clinical and operational processes. Provide actionable insights to improve performance.

Research and Evaluation: Conduct research and evaluation projects to assess the impact of healthcare interventions and programs. Collaborate with clinical and administrative teams to design and implement studies.

Compliance and Standards: Ensure compliance with relevant regulations, standards, and best practices in healthcare data management and analysis.

Collaboration: Work closely with IT, clinical, and administrative teams to identify data needs and provide analytical support. Participate in cross-functional projects and initiatives.