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Internship Data Modeler Jobs (NOW HIRING)

Together AI

Data Warehouse Engineer

San Francisco, CA · On-site

$130K - $170K/yr

Requirements * 0-4 years of professional experience (or strong internships/projects) working with ... Familiarity with data modeling concepts like SCD2 or star schemas - even if only from coursework.

Together AI

Data Warehouse Engineer

San Francisco, CA

$130K - $170K/yr

Requirements * 0-4 years of professional experience (or strong internships/projects) working with ... Familiarity with data modeling concepts like SCD2 or star schemas - even if only from coursework.

Athena LLC

Build and refine matching models to evaluate Athena's Executive Partners (XPs) and clients ... Previous internship or project experience demonstrating practical data science applications.

Athenago

Data Science Intern

Wilmington, DE

Build and refine matching models to evaluate Athena's Executive Partners (XPs) and clients ... Previous internship or project experience demonstrating practical data science applications.

Analytica

Data Engineer

Washington, DC · On-site

$129K - $155K/yr

Exposure to Databricks, Apache Spark, or distributed data processing concepts through coursework, internships, or projects * Understanding of basic data modeling and ETL/ELT concepts * Ability to ...

Analytica

Data Engineer

Washington, DC · On-site

$129K - $155K/yr

Exposure to Databricks, Apache Spark, or distributed data processing concepts through coursework, internships, or projects * Understanding of basic data modeling and ETL/ELT concepts * Ability to ...

INSPYR Solutions

Data Engineer III

Bellevue, WA · On-site

$53 - $72/hr

... modeling, pipeline development, and data warehouse design • 3+ years of non-internship professional software development experience building production services • SQL skills and experience ...

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How much do internship data modeler jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for internship data modeler in the United States is $58.71, according to ZipRecruiter salary data. Most workers in this role earn between $52.64 and $68.27 per hour, depending on experience, location, and employer.

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

AspectInternship Data ModelerData Analyst
Required CredentialsTypically pursuing or recent graduate in Data Science, Computer Science, or related fieldsOften holds a degree in Statistics, Mathematics, or related fields
Work EnvironmentInternship setting, often in tech or finance companies, focusing on data modeling tasksOffice environment, analyzing data sets, creating reports, and visualizations
Employer & Industry UsageUsed in companies developing databases, data warehouses, or software solutionsCommon across industries for business insights, marketing, finance, and operations

The Internship Data Modeler focuses on designing and developing data models during an internship, often with a learning component. In contrast, a Data Analyst interprets data, creates reports, and provides insights. While both roles require analytical skills, the internship data modeler emphasizes data structure design, whereas the data analyst emphasizes data interpretation and reporting.

What cities are hiring for Internship Data Modeler jobs? Cities with the most Internship Data Modeler job openings:
What are the most commonly searched types of Data Modeler jobs? The most popular types of Data Modeler jobs are:
What states have the most Internship Data Modeler jobs? States with the most job openings for Internship Data Modeler jobs include:
Internship Data Modeler jobs near you
Data Warehouse Engineer

Data Warehouse Engineer

Together AI

San Francisco, CA • On-site

Full-time

Posted 3 days ago

Job description

Job Summary:
Together AI is a research-driven artificial intelligence company focused on building high-performance inference compute and software platforms. They are seeking an early-career Data Warehouse Engineer to contribute to designing and operating their data warehouse, ETL pipelines, and improve data quality and governance.
Responsibilities:
• Contribute to building and maintaining a medallion/curated data warehouse stack (bronze/silver/gold) for product, usage, billing, and operational data.
• Build and maintain Airflow orchestrated pipelines and dbt transformation projects (modular, tested, documented).
• Help design analytics-ready models: SCD Type 2, star schemas, and appropriate normalization for upstream canonical layers.
• Learn and apply Master Data Management (MDM) patterns (golden records, reference data, deduping, identity resolution).
• Implement data quality checks (freshness, nulls, referential integrity, distribution drift, anomaly detection).
• Contribute to data governance habits: data stewardship, ownership, SLAs, and clear definitions for “source of truth.”
• Help build and maintain a business semantic layer (consistent metric definitions, dimensions, and reusable logic) used by notebooks/BI.
• Partner with stakeholders (Product, Engineering, Finance, GTM, Ops) to translate questions into durable datasets and metrics.
• Use SQL, Python, and Spark where scale demands it; optimize for correctness, performance, and cost.
Qualifications:
Required:
• 0–4 years of professional experience (or strong internships/projects) working with data warehouses, pipelines, or analytics engineering.
• Solid SQL fundamentals — you’re comfortable writing queries and have some exposure to window functions or dimensional modeling concepts.
• Some hands-on experience with dbt or Airflow, or strong eagerness to learn — coursework and personal projects count.
• Basic Python for scripting and data tooling; any exposure to Spark (PySpark/SQL) is a plus.
• Familiarity with data modeling concepts like SCD2 or star schemas — even if only from coursework.
• Good communication skills: you can ask clarifying questions, explain your reasoning, and work with stakeholders to understand their needs.
• High standards for data quality, reliability, and maintainability — you care about getting things right.
Company:
Together AI provides a cloud platform for developing, training, fine-tuning, and deploying generative AI models. Founded in 2022, the company is headquartered in San Francisco, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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