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JD #2122
Applications open Internship

Ai Engineer

NxtWave

  • Bengaluru, India
  • 5 LPA - 6 LPA
  • Internship
  • Posted Oct 24, 2026
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About the role

Google, the world’s leading technology company, has built a reputation for innovation, scale, and impact across a multitude of products and services. One of its most widely used offerings is Google Docs, a cloud‑based document creation and collaboration platform that powers millions of individuals, startups, and enterprises every day. Operating from its vibrant campuses in India, especially the Bengaluru office, Google fosters a culture of openness, continuous learning, and relentless problem‑solving. The company’s mission to organize the world’s information and make it universally accessible resonates strongly within the Docs team, where engineers, product managers, analysts, and designers work together to enhance user experience, improve performance, and drive new feature adoption. The Analyst role at Google Docs is a pivotal position that bridges data insights with product strategy. As an Analyst, you will dive deep into user behavior, product metrics, and market trends to uncover actionable insights that shape roadmap decisions. You will collaborate closely with product managers, engineers, and UX researchers to translate raw data into clear recommendations that improve user engagement, retention, and overall product health. This role offers exposure to large‑scale data pipelines, cutting‑edge analytical tools, and a fast‑paced environment where your work directly influences products used by billions worldwide. Key Responsibilities: 1. Collect, clean, and validate large datasets from internal data warehouses and external sources. 2. Perform exploratory data analysis to identify usage patterns, drop‑off points, and growth opportunities. 3. Build and maintain dashboards and visualizations using tools such as Looker, Tableau, or Data Studio. 4. Develop predictive models and statistical analyses to forecast user adoption and feature impact. 5. Partner with product managers to define key performance indicators (KPIs) and track progress against OKRs. 6. Conduct A/B testing design, execution, and result interpretation to guide product experiments. 7. Prepare concise, data‑driven presentations for senior leadership and cross‑functional teams. 8. Automate recurring reporting processes using SQL, Python, or R to improve efficiency. 9. Monitor data quality and implement governance best practices. 10. Stay updated with industry trends and suggest innovative analytical approaches. Tech Stack: SQL, Python (pandas, numpy), R, Looker/Tableau/Data Studio, Google BigQuery, Git, JIRA, and basic knowledge of cloud services (GCP). Growth Path: Starting as an Analyst, you can progress to Senior Analyst, Data Scientist, Product Analyst Lead, and eventually to Product Management or Analytics Leadership roles, depending on your interests and performance. Google encourages continuous upskilling through internal courses, mentorship programs, and conference sponsorships. Why Join Google Docs? You will be part of a globally recognized brand that values creativity, diversity, and impact. The role offers exposure to massive, real‑world datasets, a collaborative environment, and the chance to influence products that touch millions of users daily. Moreover, Google’s commitment to employee well‑being, flexible work arrangements, and generous benefits make it an ideal place to launch and accelerate a data‑driven career.

Eligibility & process

Who can apply

Graduates with a B.Tech/B.E/M.Tech in Computer Science, Information Technology, Electronics, or related engineering streams. Minimum CGPA/percentage of 60% (or equivalent). Eligible batch years: 2024, 2025, 2026. No active backlogs at the time of application. Candidates should have strong analytical mindset and proficiency in data manipulation tools.

Skills & stack

SQL Python Data Analysis Statistics Data Visualization Google Bigquery Looker

Selection process

  1. Round 1: Online Assessment (coding & data analysis)
  2. Round 2: Technical Interview (SQL, Python, case studies)
  3. Round 3: HR Interview (culture fit, motivations)

Prep kit

20 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (SQL, Python, Data Analysis, Statistics, Data Visualization, Google Bigquery, Looker) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion NxtWave Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 5
What is the difference between WHERE and HAVING clauses in SQL? Answer
Model answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer
Model answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer
Model answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer
Model answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer
Model answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Behavioural & HR questions 3
Why do you want to join NxtWave as a Ai Engineer?
Highlight NxtWave's market reputation, recent tech innovations, and how your skills in SQL directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
NxtWave 5 LPA - 6 LPA
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