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REQUIREMENT_ID_2367 • 3-DAY_ACTIVE_POLICY JD

Software Engineer Trainee

Company
Company American Chase
Type
Opportunity Type Internship
Salary
Stipend / Salary 12 LPA
Location
Location Bengaluru, India
Posted Date
Posted Date Today
Apply on Official Website ↗ 🤝 Connect Recruiter ↗
AM
American Chase Technical Recruiter
Talent Acquisition Partner
🏢 American Chase • Direct Recruiter Email: recruiter@americanchase.com
SQL Python Data Analysis Statistics Excel Tableau Looker Communication Problem Solving Business Acumen
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Placement Papers for Google Open Resource ↗
A collection of previous placement papers that helps candidates understand the type and difficulty of questions asked at Google.
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Google Recruitment Process Insights Open Resource ↗
Detailed experiences from candidates that outline each interview stage and preparation tips for Google.
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Google Interview Preparation Guide Open Resource ↗
Comprehensive guide covering coding, analytical, and behavioral aspects specific to Google interviews.
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Algorithm Practice Problems Open Resource ↗
A vast repository of algorithmic problems to sharpen coding skills required for Google technical rounds.

Graduates of 2025 (B.Tech/B.E., B.Sc., B.Com, MBA or equivalent) with a minimum of 60% aggregate (or CGPA 6.0/10). All engineering/technology, commerce, and science streams are eligible. No active backlogs at the time of application. Candidates should have strong analytical aptitude, basic programming knowledge, and proficiency in Excel or similar tools.

1
Round 1: Online Assessment
2
Round 2: Technical Interview
3
Round 3: HR Interview
Google, the global technology leader, has a strong presence in India with its headquarters in Bengaluru. The company is renowned for its innovative products, cutting‑edge research, and a culture that encourages curiosity, collaboration, and continuous learning. As part of the broader Google ecosystem, docs.google.com focuses on building and enhancing collaborative productivity tools that empower millions of users worldwide. The organization values data‑driven decision making, user‑centric design, and a relentless pursuit of excellence, making it an ideal place for fresh talent to grow. The Analyst role at docs.google.com is designed for recent graduates who are passionate about turning raw data into actionable insights. You will work closely with product managers, engineers, and senior analysts to understand business problems, design analytical frameworks, and deliver recommendations that influence product strategy and user experience. This position offers exposure to large‑scale data pipelines, advanced analytics tools, and a fast‑paced environment where every insight can have a direct impact on millions of users. Key responsibilities include: 1. Collecting, cleaning, and validating large datasets from multiple sources. 2. Performing exploratory data analysis to uncover trends, patterns, and anomalies. 3. Building interactive dashboards and visualizations for stakeholders. 4. Conducting statistical modeling and hypothesis testing to support product decisions. 5. Collaborating with cross‑functional teams to define metrics and success criteria. 6. Automating repetitive reporting tasks using scripting languages. 7. Presenting findings and recommendations in clear, concise formats. 8. Monitoring key performance indicators and alerting on deviations. 9. Assisting in A/B test design, execution, and analysis. 10. Continuously learning new tools and techniques to improve analytical efficiency. The tech stack typically includes SQL, Python (pandas, numpy), Tableau/Looker, and Google Cloud Platform services such as BigQuery. As you gain experience, you can progress to Senior Analyst, Data Scientist, or Product Analytics Manager roles, with opportunities to lead larger projects and mentor junior teammates. Joining Google means access to world‑class mentorship, a vibrant community of innovators, and a supportive environment that values work‑life balance, diversity, and personal growth. If you are eager to apply your analytical mindset to real‑world problems and thrive in a collaborative setting, this role offers a launchpad for a rewarding career.

American Chase — Data Analytics & SQL Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC 📖
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource ↗
COMPANY GUIDE 🎯
American Chase Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for American Chase and off-campus tech roles.

Open Resource ↗
MOCK TESTS & PAPERS 📝
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource ↗
CODING PRACTICE 💻
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource ↗
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, Excel, Tableau, Looker, Communication, Problem Solving, Business Acumen) & 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
American Chase Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
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.
Why do you want to join American Chase as a Software Engineer Trainee?
Preparation Tip: Highlight American Chase'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.
Preparation Tip: 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?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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