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Data Analytics Apprentice information

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$11

$21

$34

How much do data analytics apprentice jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for data analytics apprentice in Miami, FL is $21.82, according to ZipRecruiter salary data. Most workers in this role earn between $17.45 and $24.13 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a data analytics apprentice?

To thrive as a Data Analytics Apprentice, you need a solid understanding of statistics, data manipulation, and basic programming, often supported by foundational coursework or a related degree. Familiarity with tools such as Excel, SQL, and data visualization platforms like Tableau or Power BI is typically required. Strong analytical thinking, attention to detail, and effective communication help you interpret data and share insights clearly. These skills are vital for transforming raw data into actionable information, supporting decision-making, and learning advanced analytics techniques on the job.

What types of projects and tasks can I expect to work on as a data analytics apprentice?

As a Data Analytics Apprentice, you will typically work on a range of projects such as cleaning and organizing datasets, creating reports and visualizations, and conducting basic analyses to uncover trends or patterns. You'll often collaborate with data analysts, engineers, and business teams to support decision-making processes. Expect to use tools like Excel, SQL, or Tableau, and gradually take on more complex assignments as your skills develop. This hands-on experience is designed to build foundational skills and prepare you for more advanced data roles in the future.

What is the difference between Data Analytics Apprentice vs Data Analyst?

AspectData Analytics ApprenticeData Analyst
Required CredentialsOften entry-level, some may have a degree or certification in data-related fieldsTypically requires a degree in data science, statistics, or related fields; certifications like Google Data Analytics are common
Work EnvironmentInternship or trainee position, often in a corporate or consulting settingFull-time role in various industries, including finance, healthcare, and tech
Employer & Industry UsageUsed by companies to train and evaluate potential future analystsStandard role for analyzing data, creating reports, and supporting decision-making

The main difference is that a Data Analytics Apprentice is an entry-level trainee position designed for learning and development, while a Data Analyst is a full-fledged professional responsible for analyzing data and providing insights. Apprenticeships often serve as a stepping stone toward becoming a Data Analyst.

What does a data analytics apprentice do?

A Data Analytics Apprentice is an entry-level professional who supports data analysis tasks while learning on the job. They assist with collecting, cleaning, and interpreting data to help organizations make informed decisions. Apprentices often work under the supervision of experienced data analysts, using tools like Excel, SQL, and basic data visualization software. Their responsibilities may include creating reports, identifying trends, and helping with data-driven projects as they develop their skills.
What are the most commonly searched types of Data Analytics jobs in Miami, FL? The most popular types of Data Analytics jobs in Miami, FL are:
Data Analytics Apprentice jobs near you
Infographic showing various Data Analytics Apprentice job openings in Miami, FL as of August 2026, with employment types broken down into 100% Full Time. Highlights an 86% In-person, and 14% Hybrid job distribution, with an average salary of $45,383 per year, or $21.8 per hour.

Data Scientist / DataOps Engineer

bit schulungscenter GmbH

Miami, FL • On-site

$140 - $210/hr

Other

Posted 2 days ago

New

Job description

We are Kmeleon, consulting firm based in Miami, USA, with a dynamic and diverse team spread across the Americas and Europe. We specialize in building cutting‑edge generative AI solutions, empowering forward‑thinking enterprises to stay ahead with the transformative power of AI.

What We’re Looking For:

We’re looking for a Data Scientist / DataOps Engineer with a strong background in cloud‑based data architectures, analytics, and MLOps. You will play a vital role in designing, implementing, and maintaining scalable data solutions across Azure (primarily), AWS, and GCP—powering everything from traditional data pipelines to advanced AI/ML models.

Important:
  • We are hiring for senior roles only.
  • English proficiency at a minimum 7/10 level (spoken and written).
  • 3+ years of professional experience (not apprenticeship).
About the Role:
  • Design and optimize data pipelines on Azure, AWS, and GCP, ensuring efficient ingestion, transformation, and storage of large‑scale datasets.
  • Develop and maintain DataOps workflows, integrating with CI/CD pipelines for end‑to‑end automation of data processes.
  • Build scalable ML/AI pipelines that support training, validation, and deployment of machine learning models in production environments.
  • Collaborate on analytics solutions, assisting in data modeling, statistical analysis, and advanced AI/ML experimentation.
  • Implement robust data security and governance strategies, ensuring compliance with industry standards and best practices.
  • Troubleshoot and optimize performance across various data systems, identifying areas for continuous improvement in our architecture.
What You Bring to the Table:
  • 3+ years of hands‑on experience in DataOps, Data Engineering, or Data Science roles, with a primary focus on Azure services (Azure Data Factory, Azure Synapse, etc.).
  • Working knowledge of AWS (e.g., Glue, Redshift, EMR) and GCP (e.g., BigQuery, Dataflow) is highly desirable.
  • Proficiency in Python for data analysis, ML model development, and scripting.
  • Experience with containerization and orchestration (Kubernetes or similar) to manage scalable data processing and model deployments.
  • A strong foundation in automation and CI/CD principles, particularly in the context of data pipelines.
  • Familiarity with infrastructure as code tools (Terraform, Biceps, ARM templates) to automate provisioning and manage resources.
  • Expertise in SQL and NoSQL databases, with hands‑on experience in designing data warehouses and data lakes.
  • It is a plus Experience with LLM/advanced AI/ML model deployment and tuning for production environments.
Why Join Us?
  • Be at the forefront of the AI revolution by joining a global team that pioneers cutting‑edge data and AI solutions.
  • Competitive compensation that rewards expertise and strong communication skills.
  • Remote‑friendly environment with flexible working hours that accommodate diverse lifestyles.
  • Massive growth potential in an AI‑first startup, offering opportunities to expand into leadership roles.
  • Collaborative culture that values innovation, open communication, and mutual respect—where your ideas and contributions truly matter.
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