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Python Data Analysis Internship Jobs in Riverview, FL

Booz Allen Hamilton

Mid Data Analyst

Tampa, FL · On-site

$61K - $141K/yr

... Python, or SQL * Knowledge of how to identify new sources of data and met hods to improve data collection, analysis, and reporting * Ability to develop data pipelines and integrate data tools and ...

AEVEX

Program Data Science Analyst

Tampa, FL

Conduct exploratory data analysis, identify patterns, and generate actionable insights from ... Proficiency in Python; experience with C++, Java, or R is beneficial * Familiarity with AI/ML tools ...

AEVEX

Program Data Science Analyst

Tampa, FL · On-site

Conduct exploratory data analysis, identify patterns, and generate actionable insights from ... Proficiency in Python; experience with C++, Java, or R is beneficial * Familiarity with AI/ML tools ...

AEVEX

Program Data Science Analyst

Tampa, FL · On-site

Conduct exploratory data analysis, identify patterns, and generate actionable insights from ... Proficiency in Python; experience with C++, Java, or R is beneficial * Familiarity with AI/ML tools ...

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Python Data Analysis Internship information

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$10

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$37

How much do python data analysis internship jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for python data analysis internship in Riverview, FL is $20.07, according to ZipRecruiter salary data. Most workers in this role earn between $15.43 and $21.88 per hour, depending on experience, location, and employer.

What is a Python Data Analysis Internship?

A Python Data Analysis Internship is a temporary position, often for students or recent graduates, that provides hands-on experience in analyzing data using the Python programming language. Interns typically assist with collecting, cleaning, and interpreting large datasets, using Python libraries such as pandas, NumPy, and matplotlib. The internship is designed to help participants develop practical skills in data manipulation, statistical analysis, and data visualization. It is a great way to gain real-world experience in data science and analytics while building a professional network.

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

To thrive as a Python Data Analysis Intern, you need a solid understanding of statistics, data manipulation, and Python programming, often supported by relevant coursework or projects. Familiarity with tools such as pandas, NumPy, Jupyter Notebook, and data visualization libraries like matplotlib or seaborn is typically required. Strong analytical thinking, attention to detail, and effective communication skills help interns interpret data and share insights clearly with team members. These skills enable interns to extract actionable insights from complex datasets and effectively contribute to data-driven decision making.

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

AspectPython Data Analysis InternshipData Analyst
Required SkillsPython, data analysis, basic statisticsData analysis, SQL, Excel, Python (optional)
Work EnvironmentInternship setting, learning-focusedFull-time or part-time professional role
Experience LevelEntry-level, internshipEntry to mid-level professional
Industry UsageInternship programs, entry rolesBusiness, finance, tech, healthcare

While a Python Data Analysis Internship focuses on gaining hands-on experience with Python and data analysis tools in an internship setting, a Data Analyst role involves applying these skills professionally to analyze data, generate reports, and support decision-making in various industries.

What types of projects and tasks can I expect to work on during a Python Data Analysis Internship?

As a Python Data Analysis intern, you can typically expect to work on projects involving data collection, cleaning, and exploration using Python libraries such as Pandas and NumPy. Your daily tasks may include writing scripts to automate data processing, creating visualizations with tools like Matplotlib or Seaborn, and assisting in preparing reports or presentations based on your findings. Interns often collaborate with data scientists, analysts, and sometimes other departments to support ongoing projects and gain exposure to real-world data challenges. This hands-on experience is valuable for building both technical skills and an understanding of how data-driven decisions are made in a professional environment.
What job categories do people searching Python Data Analysis Internship jobs in Riverview, FL look for? The top searched job categories for Python Data Analysis Internship jobs in Riverview, FL are:
What cities near Riverview, FL are hiring for Python Data Analysis Internship jobs? Cities near Riverview, FL with the most Python Data Analysis Internship job openings:
Python Data Analysis Internship jobs near you
Infographic showing various Python Data Analysis Internship job openings in Riverview, FL as of June 2026, with employment types broken down into 1% As Needed, 96% Full Time, and 3% Part Time. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $41,750 per year, or $20.1 per hour.

Principal Data Architect

Raymondjames

Saint Petersburg, FL • Hybrid

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago

Job description

Job Description Summary

The Principal Data Architect is a senior enterprise architecture and strategy leader within the Enterprise Data & Analytics Architecture team. This role defines and advances the enterprise data architecture vision, target-state patterns, data platform strategy, and adoption roadmap across on-premises and cloud environments. The Principal Data Architect partners with senior technology leaders, data engineering teams, enterprise data management, analytics consumers, security, risk, compliance, and business stakeholders to deliver scalable, secure, reusable, and business-aligned data capabilities.

Job Description

This position follows our hybrid-friendly schedule, so you get the best of both worlds - flexibility and collaboration. In office days will be 2-3 per week averaging 10-12 days per month in our St Petersburg, FL Corporate Office.

Responsibilities

  • Data Lakehouse and Warehouse Architecture: Own reference architectures and design patterns for enterprise data Lakehouse and warehouse platforms, including AWS Redshift, Apache Iceberg, Oracle Exadata, S3, Glue, Lake Formation, Athena, EMR, Presto, Airflow, and related ecosystem capabilities.

  • Data Modeling and Design Leadership: Lead the design of logical, conceptual, and physical data models using ER Studio or similar tools. Establish modeling standards across normalized, dimensional, Data Vault, star, snowflake, and denormalized approaches. Resolve complex modeling issues that span multiple systems and business domains.

  • Architecture Standards and Reuse: Create and maintain data architecture principles, design standards, reusable patterns, architecture decision records, reference implementations, and best-practice guidance that can be adopted across programs.

  • Data Access and Consumption Strategy: Define enterprise data access patterns, consumption models, and fit-for-purpose tool guidance for BI, advanced analytics, operational reporting, AI/ML, data products, APIs, and self-service use cases. Recommend appropriate access controls, semantic layers, and data sharing mechanisms.

  • Platform and Technology Strategy: Evaluate, rationalize, and guide selection of data tools, storage formats, integration technologies, metadata platforms, quality tooling, lineage capabilities, and cloud-native services. Balance innovation, cost, complexity, security, vendor risk, and operational maturity.

  • Real-Time and Batch Data Architecture: Define patterns for both batch and real-time data movement, including Kafka schemas, event-driven design, data contracts, schema governance, replication, CDC, ETL/ELT, medallion architecture layers, and data quality controls across pipelines.

  • Thought Leadership and Innovation: Monitor emerging trends in cloud data platforms, lakehouse architectures, data mesh, data products, AI-ready data, metadata automation, data observability, and financial services data architecture. Recommend pragmatic adoption paths that strengthen enterprise capabilities.

  • Governance, Metadata, Lineage, and Data Quality: Partner with Enterprise Data Management and governance teams to embed metadata, lineage, data quality, cataloging, ownership, privacy classification, retention, and stewardship expectations into platform and solution architecture.


Skills

  • Must have deep, hands-on experience in wealth management, asset management, brokerage, private client services, or closely related financial services domains.

  • Proven ability to influence senior stakeholders, guide complex architectural decisions, mentor architects or senior engineers, and lead through ambiguity.

  • Expert level knowledge of Data Architecture, Data Modeling, Data Lake house and data warehouse design methodologies (star schema, snowflake schema, normalization, denormalization).

  • Proficient with database technologies: Oracle (including RAC, Exadata), SQL Server, AWS Redshift, and replication tools like Oracle Golden Gate and AWS DMS.

  • Advanced SQL, PL/SQL development, and database performance tuning skills.

  • Deep expertise in AWS Data Ecosystem-Athena, Iceberg, Lake Formation, Glue, EMR, Sagemaker, S3, Airflow, Aurora, Presto.

  • Skilled in scripting and automation (Shell, Python).

  • Data integration architecture: Ability to architect ETL/ELT, streaming, event-driven, API-based, file-based, and replication-based data flows, including data contracts, schema evolution, lineage, quality checks, and operational monitoring.

  • Data Lakehouse & Data Marketplace Architecture: Proven experience designing and operationalizing enterprise-scale data lake, Lakehouse, or data marketplace platforms, including governed data onboarding, metadata management, data product publishing.

  • AI Data Readiness & Semantic Data Enablement: Demonstrated ability to assess, structure, and curate enterprise data for AI, advanced analytics, and GenAI use cases, including defining semantic models, ontologies, knowledge graphs.

Education/Previous Experience:

  • Bachelor's degree in Computer Science, MIS, or related field.

  • 10+ years of progressive experience in data architecture, data engineering, database architecture, enterprise architecture, or large-scale data platform delivery.

Licenses/Certifications:

  • AWS or relevant cloud certification highly preferred.

Education

Bachelor's: Computer and Information Science (Required), Bachelor's: Computer Engineering

Work Experience

General Experience - 10 to 15 years

Certifications

Travel

Less than 25%

Workstyle

Hybrid

The total compensation for this position includes base salary or wages, and may include components such as additional compensation (cash or equity), discretionary bonuses, or commissions. This position is eligible for a benefits package that may include medical, dental, and vision; life insurance; critical illness insurance and accident insurance; disability benefits; retirement savings; paid time off (including vacation, holidays, and sick leave); and parental leave. Eligibility for benefits and specific offerings may vary based on position and employment status. To view more details of the benefits offered, visit Myrjbenefits.com.

At Raymond James our associates use five guiding behaviors (Develop, Collaborate, Decide, Deliver, Improve) to deliver on the firm's core values of client-first, integrity, independence and a conservative, long-term view.
We expect our associates at all levels to:
Grow professionally and inspire others to do the same
Work with and through others to achieve desired outcomes
Make prompt, pragmatic choices and act with the client in mind
Take ownership and hold themselves and others accountable for delivering results that matter
Contribute to the continuous evolution of the firm

At Raymond James - as part of our people-first culture, we honor, value, and respect the uniqueness, experiences, and backgrounds of all of our Associates. When associates bring their best authentic selves, our organization, clients, and communities thrive. The Company is an equal opportunity employer and makes all employment decisions on the basis of merit and business needs.

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