The hiring process at Tredence takes an average of 25 days when considering 1 user submitted interviews across all job titles. Candidates applying for Associate had the quickest hiring process (on average 25 days), whereas Associate roles had the slowest hiring process (on average 25 days).
First aptitude plus coding which was very difficult,the coding question was too hard and unable to crack it the complexity of teu coding question was too hard to understand .
I first received a call from the recruiter regarding the Data Engineer role. After that, the interview was scheduled with the technical team. The discussion mainly focused on my previous project experience, SQL, Python, data pipelines, ETL concepts, and basic data engineering scenarios. The interviewer asked practical questions related to how I handled data transformation, joins, aggregations, and pipeline logic in my previous work. Overall, the process was professional and technically focused.
Interview questions [1]
Question 1
Question: Explain one data engineering project you worked on recently.
I explained a project where I worked on building ETL pipelines to process large datasets, clean and transform raw data, handle duplicates and missing values, and prepare structured data for reporting and analytics. I also explained how SQL and Python were used for transformation and validation.
I applied online. I interviewed at Tredence (Pune) in June 2026
Interview
The interview was for some pricing team , where demand forecasting and things related to it would be asked however when my interview was being scheduled I clearly told the Hr I am not the guy for it but she still told it is fine and I proceeded , I told the guy the same but he started questioning for 1 hr 35 minutes despite the time scheduled was for 1 hr he did not even ask weather it is okay to go beyond time, very bad experience , this is when I told him that I am not the guy think about it if I told him I am the guy for the job he would have drilled me for 2-3 hrs.
Interview questions [1]
Question 1
R square, P value, VIFs all linear regression and demand forecasting related concepts ,