The intern will work closely with engineering and business stakeholders to design, develop, and ... Collaborate on data pipelines, ETL/ELT workflows, and analytics solutions (Databricks preferred)
The intern will work closely with engineering and business stakeholders to design, develop, and ... Collaborate on data pipelines, ETL/ELT workflows, and analytics solutions (Databricks preferred)
AI Co-Op
Wooster, OH · On-site
The intern will work closely with engineering and business stakeholders to design, develop, and ... Collaborate on data pipelines, ETL/ELT workflows, and analytics solutions (Databricks preferred)
AI Co-Op
Wooster, OH · On-site
The intern will work closely with engineering and business stakeholders to design, develop, and ... Collaborate on data pipelines, ETL/ELT workflows, and analytics solutions (Databricks preferred)
Intern Databricks Developer information
What is the difference between Intern Databricks Developer vs Intern Data Engineer?
| Aspect | Intern Databricks Developer | Intern Data Engineer |
|---|---|---|
| Primary Focus | Developing and optimizing data processing using Databricks platform | Building and maintaining data pipelines and infrastructure |
| Skills & Certifications | Knowledge of Spark, Databricks, SQL, Python; basic cloud certifications | Knowledge of ETL, SQL, cloud platforms, scripting; similar certifications |
| Work Environment | Collaborates with data science and analytics teams on Databricks platform | Works with data engineering teams on data pipelines and storage |
While both roles involve working with data and cloud platforms, the Intern Databricks Developer primarily focuses on developing data solutions within the Databricks environment, whereas the Intern Data Engineer concentrates on building and maintaining data infrastructure and pipelines across various platforms. Both roles require similar technical skills and certifications, but their day-to-day tasks and focus areas differ.
ArtiFlex Manufacturing rating
7.9
Based on 5 frontline employees who took The Breakroom Quiz
Job description
The intern will work closely with engineering and business stakeholders to design, develop, and deploy data- and AI-powered solutions that improve operational efficiency, quality analytics, and decision-making across the organization.
- Design, develop, and maintain AI and data-driven applications for manufacturing, quality, and operational analytics
- Work with large-scale datasets stored in SQL Server and cloud data platforms
- Build and optimize machine learning and Generative AI solutions, including RAG (Retrieval-Augmented Generation) systems
- Develop and deploy AI models and AI-powered applications into production environments
- Collaborate on data pipelines, ETL/ELT workflows, and analytics solutions (Databricks preferred)
- Contribute innovative ideas to solve complex, real-world manufacturing problems
- Follow Artiflex Code of Behaviors, engineering standards, and best practices
- Participate in code reviews, debugging, testing, and performance optimization
- Communicate clearly with technical and non-technical stakeholders
- Prior internship experience or minimum 1 year of relevant work experience
- Currently pursuing or recently completed a Master’s degree in Computer Science, Data Science, Information Technology, or Artificial Intelligence / Machine Learning (preferred)
- Strong programming skills in Python, SQL, and C / C++
- Experience working with large datasets and relational databases (SQL Server preferred)
- Strong understanding of modern AI trends, especially Generative AI
- Proven ability to think critically, solve problems quickly, and work independently
- Excellent communication and collaboration skills
- Familiarity with modern cloud-based data and AI platforms is preferred but not mandatory, such as:
- Lakehouse platforms (Databricks or Snowflake)
- AWS (S3, Glue, Athena, Redshift, SageMaker)
- Google Cloud Platform (BigQuery, Vertex AI, Cloud Storage)
- Azure (preferred) (Azure Data Lake, Synapse, Azure ML)
- Hands-on experience developing AI/ML models, applications, and deploying them to production
- Strong experience with RAG systems, vector databases, and embedding-based search
- Experience building, fine-tuning, or evaluating LLMs
- Hands-on experience with Generative AI frameworks (LangChain, LlamaIndex, OpenAI, etc.)
- Experience using CLI tools, Git workflows, and CI/CD pipelines
- Experience working on large, collaborative development teams
- Exposure to cutting-edge web technologies and AI-enabled applications
- Experience with UX/UI principles, design-centric approaches, and building engaging user interfaces
- Real-world experience applying AI and data engineering in manufacturing and enterprise environments
- Hands-on exposure to production-grade AI systems
- Opportunity to contribute directly to AI initiatives that impact operations and decision-making
About ArtiFlex Manufacturing
Sourced by ZipRecruiter
Industry
Motor vehicle manufacturing
Company size
501 - 1,000 Employees
Headquarters location
Grand Rapids, MI, US