Forma.ai Analytics Engineer Intern in Pune: Overview
Forma.ai is hiring an Analytics Engineer Intern through its India Campus application board in Pune. The official page describes a hybrid model with three office days and two work-from-home days, giving candidates a clear sense of the work arrangement. The role sits within the Analytics and Data Science team, which works between customers and engineering to configure a sales compensation platform. The internship focuses on implementation support, translating business needs into code, and building or improving data pipelines, architectures, and datasets using diverse customer data.
The listing is useful for candidates who want a role that connects technical work with customer-facing problem solving. It also makes clear that the application is currently accepted through the official Greenhouse form. At the same time, several details are not stated, including a minimum grade, specific graduation batch, internship duration, application deadline, and monthly stipend. Candidates should therefore rely only on the official listing and avoid assuming any missing information.
The listing includes a separately stated annual training allowance for learning and development, and it must not be presented as internship pay.
What the Analytics and Data Science Team Does
The role is part of a team that works between customers and engineering. That positioning is important because it shows the internship is not limited to coding alone. Instead, the team helps configure a sales compensation platform while handling the practical needs that arise when customer data must be used in a structured system. The intern contributes to this process by supporting new customer implementations and helping turn business requirements into code.
Key team responsibilities reflected in the listing
- Working between customers and engineering
- Configuring a sales compensation platform
- Supporting new customer implementations
- Translating business requirements into code
- Building or optimising data pipelines, architectures, and datasets
- Using diverse customer data in implementation work
The role description also points to a practical, implementation-oriented environment. Rather than describing a purely theoretical internship, the listing emphasizes direct contribution to customer-facing work. That makes the position relevant for candidates interested in how data engineering and analytics support real business systems. It also highlights why customer empathy matters: the intern is expected to understand the needs behind the requirements, not only the technical output.
Intern Responsibilities and Day-to-Day Focus
The internship responsibilities are centered on helping with new customer implementations. This means the intern may be involved when a customer is being brought into the platform and the data work needs to be set up correctly. The listing also says the intern translates business requirements into code, which shows that the role requires understanding what a customer or internal stakeholder needs and then implementing that need in a technical form. This is a strong indicator that the internship blends analysis, engineering, and communication.
How the responsibilities connect
- New customer implementations create the need for setup and adaptation.
- Business requirements must be understood before they can be coded.
- Data pipelines move and prepare data for use in the platform.
- Architectures shape how the data work is organized.
- Datasets need to be built or optimised for customer-specific use.
The role also implies that the intern will work across disciplines. Since the team sits between customers and engineering, the intern may need to communicate clearly with people who think about the problem in different ways. That is why the listing includes communication across disciplines and customer empathy among the required skills. These are not separate from the technical work; they support it by helping the intern understand requirements and respond to them accurately.
The overall picture is of an internship that values both implementation and collaboration. It is not presented as a narrow coding assignment, because the responsibilities include customer implementation, requirement translation, and pipeline work. Candidates reading the listing should therefore view the role as a combination of analytics engineering, data handling, and cross-functional coordination.
Skills Required and Helpful Technical Experience
The listing identifies several required skills for the Analytics Engineer Intern. The first is Python development, which suggests the role expects the intern to write and work with Python code. The listing also mentions SQL and/or Pandas, showing that data manipulation and querying are part of the expected skill set. In addition, the intern should understand automated data ingestion and ETL/ELT pipelines, which are central to moving and transforming data in a structured way.
Beyond technical skills, the listing emphasizes communication across disciplines and customer empathy. These requirements matter because the role sits between customers and engineering. The intern must be able to understand business requirements, communicate clearly, and work in a way that reflects the customer’s needs. This makes the position suitable for candidates who can combine technical execution with thoughtful collaboration.
Required skills mentioned in the listing
- Python development
- SQL and/or Pandas
- Automated data ingestion
- ETL/ELT pipelines
- Communication across disciplines
- Customer empathy
The listing also names some additional skills that are useful, though not required. These include PySpark, Databricks, and API experience. Because these are described as useful additional skills, they can strengthen an application, but they are not presented as mandatory. Candidates should treat them as helpful background rather than a requirement that must be met in every case.
Work Model, Location, and Application Details
The official page places the internship in Pune and specifies a hybrid model. The schedule is clearly described as three office days and two work-from-home days. This is one of the few logistical details provided, so it is important for candidates to note it exactly as written. The listing does not add any further location-based conditions, so no additional assumptions should be made about travel, relocation, or office expectations.
The application process is currently open through the official Greenhouse form. The form requests several pieces of information, including education details, school and college marks, branch, home location, and a resume. These fields show that the application is designed to collect both academic and personal background information relevant to the role. Since the form asks for marks and branch details, applicants should prepare those items before starting the application.
Information requested in the form
- Education details
- School marks
- College marks
- Branch
- Home location
- Resume
The listing also includes company-level benefits, but it does not clearly state which of those benefits apply to interns. That means candidates should confirm the applicability of any listed benefits before treating them as part of the internship package. The same caution applies to the annual training allowance, which is described separately for learning and development and must not be presented as internship pay. Because the listing does not state a monthly stipend, applicants should avoid assuming compensation details that are not explicitly provided.
Benefits, Allowance, and What Is Not Stated
The listing mentions company-level benefits, but candidates should confirm which of those benefits apply to interns. This is an important distinction because not every benefit listed at the company level necessarily extends to an internship. The content therefore supports a careful reading of the page rather than a broad assumption that all benefits are included. For applicants, the safest approach is to treat the benefits section as informative but not automatically internship-specific.
Another important detail is the annual training allowance. The content states that this allowance is for learning and development and must not be presented as internship pay. That distinction matters because it separates a development-related allowance from compensation for the internship itself. Since the listing does not state a monthly stipend, it would be incorrect to describe the allowance as pay or to infer a stipend amount from it.
Details the listing does not state
- Minimum grade
- Specific graduation batch
- Internship duration
- Application deadline
- Monthly stipend
Frequently Asked Questions
Where is the Analytics Engineer Intern role located?
The role is listed through Forma.ai’s India Campus application board in Pune. The official page describes a hybrid model with three office days and two work-from-home days. No additional location conditions are stated in the official listing.
What are the main responsibilities of the internship?
The intern contributes to new customer implementations, translates business requirements into code, and builds or optimises data pipelines, architectures, and datasets. The work uses diverse customer data and involves collaboration across disciplines. These responsibilities are central to the role description.
Which skills are required for the role?
Required skills include Python development, SQL and/or Pandas, automated data ingestion, ETL/ELT pipelines, communication across disciplines, and customer empathy. The listing also mentions PySpark, Databricks, and API experience as useful additional skills. These are helpful but not presented as mandatory.
What information does the application form ask for?
The form requests education details, school and college marks, branch, home location, and a resume. These fields suggest the application collects both academic and background information. The official Greenhouse form is the current application method.
Does the listing mention stipend, duration, or eligibility cutoffs?
No. The content does not state a minimum grade, specific graduation batch, internship duration, application deadline, or monthly stipend. It also notes that the annual training allowance is for learning and development and must not be presented as internship pay.
Official application
View the official Forma.ai listing and apply here. Check the live page for updates before submitting your application.
