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REQUIREMENT_ID_153 • 3-DAY_ACTIVE_POLICY

Software Engineer I

Company
Company LG Ad Solutions
Type
Opportunity Type Internship
Salary
Stipend / Salary 4 - 8 LPA
Location
Location Bangalore, Karnataka
Posted Date
Posted Date Sep 09, 2026
Python Scala Go C++ JavaScript Data Structures Algorithms MySQL Redis MongoDB HDFS Spark Databricks AWS Kubernetes Git CI/CD Distributed Systems Data Pipelines
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Aptitude and Logical Reasoning Practice Open Resource ↗
Helps sharpen analytical thinking and problem‑solving skills essential for coding interviews.
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Interview Preparation and Coding Challenges Open Resource ↗
Provides a collection of coding problems and interview questions to build confidence.
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Project and System Design Resources Open Resource ↗
Offers guidance on building real‑world projects and designing scalable systems.
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Algorithmic Coding Practice Open Resource ↗
Offers a vast set of coding problems to improve algorithmic proficiency.

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (B.E./B.Tech./B.Sc./M.E./M.Tech./M.Sc. or equivalent). No specific CGPA or percentage requirement mentioned. Freshers and experienced candidates are eligible. No backlog policy stated.

1
Round 1: Technical coding interview (DSA)
2
Round 2: System design / technical interview (distributed systems & big data)
3
Round 3: HR interview
LG Ad Solutions is a leading player in the digital advertising ecosystem, delivering high‑performance ad‑serving, targeting, and measurement solutions to global brands. With a presence in multiple markets, the company leverages cutting‑edge technologies to process billions of events per day, ensuring real‑time relevance and accuracy for advertisers. The Bangalore office serves as a hub for engineering innovation, where teams collaborate across product, data science, and infrastructure to build scalable systems that power the company’s advertising platform. The Software Engineer I role is an entry‑level position designed for freshers and early‑career professionals who are passionate about distributed systems, big data, and cloud‑native development. As a core member of the ad‑serving team, you will design, develop, and maintain high‑throughput services that handle ad requests, perform audience targeting, and collect measurement data. Your work will directly impact the latency and reliability of the platform, making it essential to write clean, testable code and participate in rigorous code reviews. Key responsibilities include: 1. Implementing new features and bug fixes for ad‑serving pipelines using languages such as Python, Scala, or Go. 2. Building data pipelines that ingest, transform, and store large volumes of event data in MySQL, MongoDB, or HDFS. 3. Collaborating with data scientists to integrate targeting models and measurement algorithms. 4. Optimizing existing services for performance, scalability, and cost efficiency on AWS and Kubernetes. 5. Writing unit, integration, and performance tests to ensure code quality. 6. Participating in continuous integration and deployment workflows. 7. Troubleshooting production incidents and performing root‑cause analysis. 8. Contributing to architectural discussions around distributed systems and micro‑services. 9. Mentoring junior teammates and sharing knowledge on best practices. 10. Keeping abreast of emerging technologies in cloud, big data, and advertising. Tech stack: Python/Scala/Go/C++/JavaScript, MySQL, Redis, MongoDB, HDFS, Spark, Databricks, AWS, Kubernetes, Git, CI/CD pipelines. Growth path: Starting as Software Engineer I, you can progress to Software Engineer II, Senior Engineer, Tech Lead, or Architecture roles within 3–5 years, depending on performance and expertise. The company encourages continuous learning through internal workshops, conference sponsorships, and access to online learning platforms. Why join LG Ad Solutions? The role offers exposure to large‑scale, real‑time systems that drive billions of dollars in advertising revenue. You’ll work alongside seasoned engineers, gain hands‑on experience with cutting‑edge technologies, and have a clear career trajectory. The company’s culture values innovation, collaboration, and work‑life balance, making it an ideal environment for early‑career talent to grow.

LG Ad Solutions — 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 🎯
LG Ad Solutions Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for LG Ad Solutions 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 (Python, Scala, Go, C++, JavaScript, Data Structures, Algorithms, MySQL, Redis, MongoDB, HDFS, Spark, Databricks, AWS, Kubernetes, Git, CI/CD, Distributed Systems, Data Pipelines) & 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
LG Ad Solutions 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 LG Ad Solutions as a Software Engineer I?
Preparation Tip: Highlight LG Ad Solutions's market reputation, recent tech innovations, and how your skills in Python 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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