Success at Grammarly requires a blend of technical mastery and the ability to act as a strategic partner. Approach your preparation by focusing on how your technical output enables better decision-making for the business.

• Role-related knowledge: You must demonstrate high proficiency in SQL and data visualization tools. Interviewers look for clean, efficient code and the ability to choose the right analytical method for the specific question at hand.
• Problem-solving ability: You will be evaluated on your process. Can you break down a vague, high-level business problem into measurable, technical steps? Show your work by explaining your assumptions clearly.
• Leadership and Communication: Even as an analyst, you are a leader of insights. You must demonstrate that you can influence stakeholders by presenting data in a way that is both accurate and persuasive.
• Culture fit: Grammarly values empathy and collaboration. Show that you are a team player who is eager to learn from others and contribute to a supportive, high-performance environment.

The interview process at Grammarly is designed to be comprehensive and rigorous. It typically begins with a recruiter screen, followed by a technical assessment—usually focused on SQL and data manipulation—to ensure you have the necessary baseline skills. If successful, you will move to a virtual onsite phase consisting of multiple rounds covering behavioral, technical, and product-case interviews.

The process is structured to test your endurance, clarity of thought, and ability to communicate under pressure. While the process can be lengthy, it is intended to give you a full picture of the team and give the team a full picture of your capabilities. Expect to interact with various stakeholders, including potential peers and cross-functional partners.

This timeline provides a high-level view of the stages you will encounter. Use it to pace your preparation; do not attempt to cram all your study into the final days. Instead, treat each stage as a milestone, focusing your energy on the specific core competencies—technical or behavioral—required for that round.

Technical Rigor

This area is non-negotiable. You are expected to be fluent in SQL and comfortable with data modeling. Strong performance looks like writing code that is not only correct but also readable and optimized for performance.

Be ready to go over:

• SQL Joins and Aggregations – Mastery of complex joins and nested subqueries.
• Data Modeling – Understanding how to structure data for efficient querying.
• Analytical Methods – Knowing when to use specific statistical tests or A/B testing frameworks.
• Advanced concepts – Exposure to cloud-based data warehouses and large-scale data processing tools.

Example scenarios:

• "Given these two tables, how would you find the top 10 users by engagement?"
• "How would you design a schema for a new user activity tracking feature?"

Analytical Intuition

This evaluates your ability to turn business goals into analytical frameworks. You are being tested on how you connect the dots between raw data and product strategy.

Be ready to go over:

• Metric Definition – How to build a North Star metric for a product.
• Root Cause Analysis – Systematically narrowing down why a metric changed.
• Experimentation – Planning a test, defining success criteria, and identifying potential biases.

Example scenarios:

• "A key metric has flatlined; walk me through your investigative process."
• "What metrics would you prioritize for a user onboarding funnel?"

As a Data Analyst at Grammarly, your primary responsibility is to act as the "eyes and ears" of the product team. You will spend your day querying large datasets to answer questions like, "Are users finding value in this specific feature?" or "How does this change impact our long-term retention?"

You will be responsible for creating dashboards, running ad-hoc queries, and presenting your findings to stakeholders. Collaboration is key; you will often work alongside engineers to ensure data accuracy and with product managers to validate hypotheses. You are expected to be an advocate for data-informed decision-making across the organization.

A strong candidate for this role possesses both the hard technical skills to handle massive data and the soft skills to communicate insights effectively.

• Must-have skills:
  • Proficiency in SQL (advanced queries, window functions).
  • Experience with data visualization tools (e.g., Tableau, Looker).
  • Strong foundation in statistical analysis and A/B testing.
  • Ability to translate business requirements into technical specifications.
• Nice-to-have skills:
  • Proficiency in Python or R for advanced data manipulation.
  • Experience working with large-scale cloud data platforms.
  • Prior experience in a product-focused, high-growth tech environment.

Q: How long does the interview process typically take? The process can be lengthy, often spanning several weeks due to the number of rounds. Stay organized and maintain communication with your recruiting point of contact.

Q: What differentiates successful candidates? Successful candidates are those who balance technical accuracy with a deep understanding of user behavior. Don't just show your code; explain the business impact of your findings.

Q: What is the work culture like at Grammarly? The culture is highly collaborative and supportive. You will be expected to work closely with cross-functional teams, so demonstrate that you are a good listener and an effective communicator.

Q: Can I work remotely? Expectations around location can vary by specific team and role. Always verify the current location requirements for the specific position you are interviewing for during your initial screen.

• Structure your answers: Use the STAR method (Situation, Task, Action, Result) for behavioral questions to keep your responses concise and impactful.
• Think aloud: During technical rounds, explain your thought process as you code. This helps the interviewer understand your logic, even if you run into a minor syntax error.
• Prepare questions for them: Use the end of your interviews to ask about the team’s current challenges or the data infrastructure. It shows genuine interest and strategic thinking.
• Stay persistent: The process can be bureaucratic. If you experience delays, reach out politely to your recruiter to keep the momentum going.

The Data Analyst role at Grammarly is a unique opportunity to shape the future of digital communication. By focusing on your technical fluency in SQL, honing your product intuition, and preparing to communicate clearly about complex data, you will be well-positioned to succeed.

Remember that every interview is an opportunity to showcase not just your skills, but your potential as a teammate. Stay engaged, keep your preparation structured, and leverage the insights provided here to guide your study. You have the potential to make a significant impact at Grammarly—prepare with confidence and take the next step in your career.

The salary data provided represents market expectations for this role. Use this to ensure your compensation expectations are aligned with the seniority of the position and your specific experience level.