I applied online. The process took 2 months. I interviewed at Altimetrik (Chennai) in Dec 2023
Interview
Worst experience with the interview process.
I cleared 1 test and 3 rounds of interviews including client round over a period of 2months. Interview difficulty was average. Interviewers were good.But the HR response is really slow.
After clearing all the rounds even client,I was put on hold because of workx was not aligned with the position.(After making me wait for 2 months,workx was the reason given)
I would not recommend this company at all.
Interview questions [1]
Question 1
basic python programs
Sql queries
data warehousing concepts
data engineering concept
first L1 round asked pyspark, sql queries, python program
then scenario based questions about project work. concepts and questions on snowflake cloud, query optimization, monitoring, etl/elt difference, joins, using cte write the query
I applied through a recruiter. I interviewed at Altimetrik (Hyderābād) in Mar 2026
Interview
Initial Screening (HR / Recruiter Round)
This is a quick discussion to understand your background, experience, and expectations.
They typically ask about:
Your current role and projects
Tech stack (like PySpark, SQL, AWS, etc.)
Notice period and salary expectations
2. Technical Round 1 (SQL + Basics)
This round mainly checks your fundamentals.
You can expect:
SQL problems (joins, window functions, aggregations)
Data cleaning or transformation questions
Basic Python or PySpark questions
Example:
Find nth highest salary
Remove duplicates
Identify consecutive records
3. Technical Round 2 (Data Engineering Concepts)
This is more in-depth and practical.
Topics usually include:
Data pipeline design
ETL/ELT concepts
Batch vs streaming
Partitioning, bucketing
Data lakes vs data warehouses
They may ask:
How you designed a pipeline using Spark/Airflow
Handling late-arriving data
Performance optimization techniques
4. System Design Round (Important for 3+ yrs experience)
Here they test how you think and design systems.
Typical questions:
Design a data pipeline for a telecom or e-commerce system
Handle large-scale data ingestion (Kafka → S3 → Redshift)
Data quality and monitoring
Focus areas:
Scalability
Fault tolerance
Cost optimization
5. Managerial / Behavioral Round
This round checks how you work in a team.
Common questions:
Challenges you faced in a project
How you handled failures in pipelines
Working with stakeholders
The first round was technical and the interviewer started with asking me to write some python code on a compiler while sharing the screen, it was a leetcode question easy one.