- About Databricks
- Types of Internships Available
- Explore Opportunities
- Strategies to Win this Databricks Internship
- Resume Writing Tips for Databricks
- General Eligibility Criteria
- Understanding Internship Compensation: Are Internships Paid?
- Top 3 Interview Preparation Questions & Sample Answers
About Databricks
Databricks is a leading data and AI company that provides a cloud-based platform to help enterprises build, scale, and govern data and AI solutions, including generative AI and machine learning models. Founded in 2013 by the creators of Apache Spark, Databricks pioneered the data lakehouse concept, combining the capabilities of data warehouses and data lakes. As a Software Engineering intern at Databricks, you would join a team of engineers to build features for the Databricks platform, manage end-to-end projects, and learn about scaling a platform while maintaining quality and security. Databricks offers internship programs across multiple offices, providing opportunities for students graduating in 2025 or 2026 with degrees in Computer Science, Engineering, or related fields.
Types of Internships Available
- Software Engineering Internship: Work on building features for the Databricks platform, managing end-to-end projects, and learning about scaling a platform while maintaining quality and security. Available programs: Winter 16-week co-op, Summer 16-week co-op, or Summer 12-week internship.
- Data Science Internship: Join the Data team to turn Databricks business and operations data into insights for product design, customer strategies, and engineering optimizations.
- Manage projects from start to finish, including data exploration, presenting insights, and deploying algorithms.
- Data Engineering Internship: Build and deliver data solutions and products to influence decision-making for business teams.
- Machine Learning Internship: Work on developing and implementing machine learning models and algorithms.
- Cloud Infrastructure Internship: Assist in managing and optimizing Databricks’ cloud-based infrastructure.
- Product Management Internship: Gain experience in product development and strategy within the data and AI industry.
- UX/UI Design Internship: Contribute to the design and user experience of Databricks’ products and interfaces.
- Research and Development Internship: Participate in cutting-edge research and development projects in data and AI technologies.
- Sales and Marketing Internship: Support sales and marketing efforts for Databricks’ products and services.
- IT Internship: Assist in managing internal IT systems and infrastructure.
Explore Opportunities
You can find information about Databricks internships at the following URL: Databricks Internships.
Strategies to Win this Databricks Internship
- Develop strong programming skills: Focus on Python, Java, or Scala, as these are key languages used at Databricks. For example, create a machine learning project using PySpark to demonstrate your proficiency in both Python and big data processing.
- Gain experience with Apache Spark: Familiarize yourself with this open-source analytics engine for big data processing. You could contribute to an open-source Spark project or build a data pipeline using Spark to showcase your skills.
- Enhance your knowledge of data science and machine learning: Databricks is at the forefront of these fields. Consider taking online courses or participating in Kaggle competitions to build your expertise and portfolio.
- Showcase your problem-solving abilities: Databricks values candidates who can tackle complex challenges. Prepare for technical interviews by practicing algorithmic problems, especially those involving data structures and dynamic programming.
- Demonstrate your passion for data and AI: Engage in relevant projects or research outside of your coursework. For instance, you could start a blog discussing recent developments in the field of data lakehouse architecture.
- Highlight your teamwork and communication skills: Databricks emphasizes collaboration. Participate in hackathons or group projects to showcase your ability to work effectively in a team environment.
- Prepare for a rigorous interview process: Databricks’ interview process typically includes multiple rounds, including a coding assessment and technical interviews. Practice coding problems regularly and be prepared to explain your thought process clearly.
- Network with Databricks employees: Attend tech meetups, conferences, or webinars where Databricks employees might be present. Building connections can provide valuable insights and potentially give you an edge in the application process.
- Familiarize yourself with Databricks’ products and culture: Research the company’s lakehouse platform, recent innovations, and company values. During interviews, demonstrate your understanding of how Databricks is revolutionizing the data and AI industry.
- Tailor your resume and application: Customize your resume to highlight skills and experiences most relevant to the specific Databricks internship you’re applying for. For example, if applying for a Data Engineering internship, emphasize your experience with data pipelines and ETL processes.
Resume Writing Tips for Databricks
- Highlight experience with Apache Spark and data lakehouse architecture:
- Showcase any projects or coursework that involved using Apache Spark or working with data lakes and data warehouses. For example: “Developed a scalable data pipeline using Apache Spark to process and analyze 1TB of social media data, implementing data lakehouse principles to optimize storage and query performance for a university research project.”
- Emphasize machine learning and AI skills:
- Demonstrate your proficiency in machine learning algorithms and AI technologies relevant to Databricks’ focus areas. For instance: “Implemented a deep learning model using TensorFlow to predict customer churn for a local startup, achieving 92% accuracy and presenting findings to stakeholders. Leveraged Databricks’ MLflow for experiment tracking and model versioning.”
- Showcase collaborative projects and open-source contributions:
- Databricks values teamwork and community involvement. Highlight group projects or contributions to open-source initiatives. Example: “Contributed to an open-source PySpark project on GitHub, implementing a new data transformation feature that was merged into the main repository. Collaborated with a global team of developers, improving code quality and documentation.”
General Eligibility Criteria
Requirement Type | Requirement Detail |
---|---|
Enrollment-Level | You must be pursuing a degree in Computer Science, Engineering, or a related field, typically graduating in fall 2025 or spring 2026. |
GPA | A minimum GPA of 3.0 may be required, though this can vary. |
Work Authorization | Eligibility to work in the desired location of the internship. |
Previous Experience | Strong proficiency in general-purpose programming languages such as Python, Java, or C++ is required. Good understanding of algorithms, data structures, and object-oriented programming principles is expected. |
It’s important to note that these requirements may vary depending on the specific internship position and can change over time. Always refer back to the original job posting for the most up-to-date and accurate eligibility criteria for the internship you’re interested in.
Understanding Internship Compensation: Are Internships Paid?
Software Engineer interns at Databricks can expect to earn between $46.60 to $54.00 per hour, depending on location and specific role. This translates to monthly salaries ranging from approximately $8,077 to $9,360. In addition to the base salary, Databricks typically offers housing stipends of around $2,500 per month and relocation assistance of about $700. Some internships may also include additional benefits such as transportation allowances or company-provided relocation support.
Disclaimer: Please note that internship details, including compensation and benefits, may change over time. It’s essential to carefully review the specific internship listing and ask clarifying questions during the recruitment process to get the most up-to-date and accurate information about the internship you’re interested in.
Top 3 Interview Preparation Questions & Sample Answers
- Why do you want to work at Databricks?
- Sample response: “I’m passionate about big data and AI, and Databricks is at the forefront of these fields. Your innovative data lakehouse architecture and contributions to Apache Spark align perfectly with my interests. I’m excited about the opportunity to work on cutting-edge projects that have a real impact on how businesses handle and analyze data at scale.”
- Explain the difference between Azure Databricks and Databricks.
- Sample response: “Databricks is the core platform that offers a unified analytics environment for data engineering, data science, and machine learning. Azure Databricks is a version of this platform specifically optimized for Microsoft Azure cloud services. While they share the same underlying technology, Azure Databricks provides seamless integration with other Azure services and is managed through the Azure portal, making it easier for organizations already using Azure to adopt and scale their data analytics capabilities.”
- How do you ensure a deployed model remains up to date?
- Sample response: “To keep a deployed model up to date, I would implement a continuous monitoring system that tracks the model’s performance metrics over time. This would include setting up automated retraining pipelines that trigger when performance drops below a certain threshold. Additionally, I’d use techniques like A/B testing to compare the current model against newer versions, and implement a version control system for easy rollback if needed. Regular reviews of the model’s input data distribution would also help identify concept drift early on.”