L&T Technology Services Limited Data Engineer Interview Questions + Guide in 2025

L&T Technology Services Limited is a leading global engineering services company that integrates advanced technologies to deliver innovative solutions across various industries.

The Data Engineer role at L&T Technology Services involves designing, building, and managing data pipelines and architectures that leverage Azure cloud services. Key responsibilities include working extensively with Databricks, PySpark, and Azure Data Factory to ensure efficient data ingestion, processing, and analysis. A successful candidate will possess strong programming skills in Python and SQL, alongside hands-on experience in building end-to-end data solutions. Familiarity with distributed data processing frameworks, data governance, and CI/CD pipeline implementation using Azure DevOps is crucial. Candidates should embody a growth mindset, demonstrating the ability to adapt to new technologies and methodologies in a fast-paced environment.

This guide will empower you to prepare effectively for your interview by highlighting the essential skills and responsibilities associated with the Data Engineer role at L&T Technology Services Limited.

The interview process for a Data Engineer at L&T Technology Services Limited is structured to assess both technical and interpersonal skills, ensuring candidates are well-rounded and fit for the role. The process typically consists of several key stages:

1. Initial Screening

The first step is an initial screening, which may be conducted via a phone call or video interview. During this stage, a recruiter will evaluate your resume and discuss your background, skills, and motivations for applying. This is also an opportunity for you to ask questions about the company culture and the specifics of the Data Engineer role.

2. Technical Assessment

Following the initial screening, candidates will undergo a technical assessment. This may include an online coding test focused on programming languages such as Python and SQL, as well as questions related to data processing frameworks like PySpark and Databricks. The assessment aims to evaluate your problem-solving abilities and your understanding of data engineering concepts, including building and optimizing data pipelines.

3. Technical Interview

Candidates who pass the technical assessment will be invited for one or more technical interviews. These interviews typically last around an hour and are conducted by senior data engineers or technical leads. Expect in-depth discussions about your previous projects, hands-on experience with Azure services, and your approach to data architecture and ETL processes. You may also be asked to solve coding problems on the spot, demonstrating your proficiency in relevant technologies.

4. Managerial Interview

The next stage is a managerial interview, where you will meet with a hiring manager or team lead. This round focuses on your past experiences, leadership qualities, and how you handle team dynamics and project challenges. Expect scenario-based questions that assess your problem-solving skills and your ability to work collaboratively in a team environment.

5. HR Interview

The final stage of the interview process is the HR interview. This round typically covers topics such as salary expectations, company policies, and your long-term career goals. It’s also an opportunity for you to discuss any remaining questions you may have about the role or the company.

As you prepare for your interview, it’s essential to be ready for a variety of questions that will test your technical knowledge and interpersonal skills. Here are some of the types of questions you might encounter during the interview process.

Here are some tips to help you excel in your interview.

Showcase Your Technical Expertise

As a Data Engineer, you will be expected to demonstrate a strong command of technical skills, particularly in Azure Databricks, PySpark, and SQL. Be prepared to discuss your hands-on experience with these technologies in detail. Highlight specific projects where you built or optimized data pipelines, and be ready to explain the architecture and design choices you made. This is your opportunity to show not just what you know, but how you apply that knowledge in real-world scenarios.

Prepare for Scenario-Based Questions

Expect to encounter scenario-based questions that assess your problem-solving abilities and technical acumen. These questions may involve troubleshooting a data pipeline issue or optimizing a data processing task. Practice articulating your thought process clearly and logically, as interviewers will be looking for your ability to think critically and approach challenges methodically.

Emphasize Your Project Experience

Your past projects are a goldmine of information that can set you apart from other candidates. Be ready to discuss at least two end-to-end data analytics projects you have worked on, particularly those involving Databricks and Azure services. Focus on your role, the challenges you faced, and the impact your work had on the organization. This not only demonstrates your technical skills but also your ability to deliver results.

Understand the Company Culture

L&T Technology Services values collaboration and innovation. Familiarize yourself with their work culture and be prepared to discuss how you can contribute to a team-oriented environment. Share examples of how you have successfully collaborated with cross-functional teams in the past, and express your enthusiasm for working in a dynamic, agile setting.

Brush Up on Soft Skills

While technical skills are crucial, soft skills such as communication, teamwork, and adaptability are equally important. Be prepared to discuss how you handle team dynamics, manage conflicts, and adapt to changing project requirements. Use specific examples to illustrate your points, as this will help convey your interpersonal skills effectively.

Practice Coding and Technical Questions

Given the technical nature of the role, you may be asked to solve coding problems during the interview. Brush up on your coding skills, particularly in Python and SQL. Practice common data manipulation tasks and algorithms that are relevant to data engineering. Being able to write clean, efficient code on the spot will demonstrate your proficiency and confidence.

Be Ready for HR Questions

The final round will likely include HR questions that assess your fit within the company. Prepare to discuss your career goals, why you want to work at L&T Technology Services, and how you align with their values. This is also a good time to ask insightful questions about the company and the team you would be joining, showing your genuine interest in the role.

By following these tips and preparing thoroughly, you will position yourself as a strong candidate for the Data Engineer role at L&T Technology Services. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at L&T Technology Services Limited. The interview process will likely focus on your technical skills, particularly in data engineering, cloud technologies, and programming. Be prepared to discuss your past projects in detail, as well as demonstrate your problem-solving abilities and understanding of data architectures.

Technical Skills

1. Can you explain the architecture of a data pipeline you have built in the past?

This question assesses your practical experience in designing data pipelines and your understanding of data flow.

How to Answer

Discuss the components of the pipeline, the technologies used, and the challenges faced during implementation. Highlight your role in the project and the impact it had on the organization.

Example

“I designed a data pipeline using Azure Data Factory and Databricks to ingest and process data from multiple sources. The pipeline utilized Delta Lake for storage, ensuring data reliability and performance. My role involved optimizing the ETL processes, which reduced data processing time by 30%.”

2. What is your experience with Azure Databricks and how have you utilized it in your projects?

This question evaluates your familiarity with Azure Databricks and its applications in data engineering.

How to Answer

Provide specific examples of projects where you used Databricks, focusing on the features you leveraged and the outcomes achieved.

Example

“In my last project, I used Azure Databricks to process large datasets for real-time analytics. I implemented PySpark for data transformation and utilized the Unity Catalog for data governance, which improved data accessibility and compliance.”

3. How do you handle data quality issues in your data pipelines?

This question tests your understanding of data quality management and your problem-solving skills.

How to Answer

Discuss the strategies you employ to ensure data quality, such as validation checks, monitoring, and error handling.

Example

“I implement data validation checks at various stages of the pipeline to catch anomalies early. Additionally, I set up monitoring alerts to notify the team of any data quality issues, allowing us to address them proactively.”

4. Describe your experience with SQL and how you have used it in data engineering tasks.

This question assesses your SQL proficiency and its application in data engineering.

How to Answer

Share specific examples of SQL queries you have written for data manipulation, reporting, or analysis.

Example

“I frequently use SQL for data extraction and transformation tasks. For instance, I wrote complex queries to join multiple tables and aggregate data for reporting purposes, which helped stakeholders make informed decisions based on accurate insights.”

5. Can you explain the concept of Delta Lake and its advantages?

This question evaluates your knowledge of modern data storage solutions and their benefits.

How to Answer

Discuss the features of Delta Lake, such as ACID transactions, schema enforcement, and time travel, and explain how they enhance data reliability.

Example

“Delta Lake provides ACID transactions, which ensure data integrity during concurrent writes. Its schema enforcement feature prevents data corruption, and time travel allows us to access historical data versions, making it easier to audit changes.”

Programming and Scripting

1. What programming languages are you proficient in, and how have you applied them in your work?

This question assesses your programming skills and their relevance to data engineering.

How to Answer

Mention the languages you are comfortable with, particularly Python, and provide examples of how you have used them in data engineering tasks.

Example

“I am proficient in Python and have used it extensively for data processing tasks. For example, I wrote scripts to automate data ingestion from APIs, which significantly reduced manual effort and improved data availability.”

2. How do you optimize the performance of your data processing jobs?

This question tests your understanding of performance tuning in data engineering.

How to Answer

Discuss the techniques you use to optimize performance, such as partitioning, caching, and parallel processing.

Example

“I optimize data processing jobs by partitioning large datasets to improve query performance. Additionally, I leverage caching in Databricks to speed up repeated queries, which has led to a noticeable reduction in processing time.”

3. Can you describe a challenging technical problem you faced and how you resolved it?

This question evaluates your problem-solving skills and technical expertise.

How to Answer

Share a specific challenge, the steps you took to address it, and the outcome of your efforts.

Example

“I faced a challenge with slow data processing times due to inefficient queries. I analyzed the query execution plan and identified bottlenecks. By rewriting the queries and adding appropriate indexes, I improved the processing speed by over 50%.”

4. What is your experience with CI/CD pipelines in data engineering?

This question assesses your familiarity with DevOps practices in the context of data engineering.

How to Answer

Discuss your experience with setting up CI/CD pipelines, the tools you used, and the benefits realized.

Example

“I have implemented CI/CD pipelines using Azure DevOps to automate the deployment of data processing jobs. This approach has streamlined our release process and reduced deployment errors, allowing for faster iterations and improved collaboration among team members.”

5. How do you ensure the security of data in your engineering processes?

This question tests your understanding of data security practices.

How to Answer

Discuss the measures you take to protect data, such as encryption, access controls, and compliance with regulations.

Example

“I ensure data security by implementing role-based access controls and encrypting sensitive data both at rest and in transit. Additionally, I regularly review our security policies to ensure compliance with industry standards and regulations.”