As with every marathon, the last mile is the toughest. It is here that enterprises lose the strength and resolve to take analytics beyond insight generation and use them to generate value. That’s where we saw a gap waiting to be filled - in activating data and operationalizing insights for real, tangible business impact. We’re focused on bridging the gap between insights delivery and value realization, partnering with our clients to help them cross the last-mile gap in analytics. This DNA pushes our ecosystem to go beyond possible, helping our clients re-think their limitations and overcome their norms of ‘possible’.
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What employees say
+ Enthusiastic and ambitious work culture. Tredence enables everyone with the tools, means and the backing one needs to succeed and grow.
− As a fast growing organization, baseline expectations would be to learn and adapt fast, be on the toes and fail fast. Not a con but the rapid pace in work is not for all.
Recent Glassdoor reviews · 1,612 total
Pros: Enthusiastic and ambitious work culture. Tredence enables everyone with the tools, means and the backing one needs to succeed and grow.
Cons: As a fast growing organization, baseline expectations would be to learn and adapt fast, be on the toes and fail fast. Not a con but the rapid pace in work is not for all.
View on GlassdoorPros: Great opportunity to learn and upskill
Cons: It's part and parcel every company to have cons. Nothing Major concern
View on GlassdoorPros: Great learning curve, especially for people early in their careers. There are plenty of opportunities to work with different technologies and solve real-world business problems. Good and talented people. Colleagues are generally supportive, collaborative, and willing to help. Projects are generally okay and provide decent exposure to different clients, domains, and technologies. Good place to build a strong foundation in data and analytics, depending on the project you are assigned to.
Cons: Work-life balance can be poor in certain projects, with long working hours and tight deadlines. The experience varies significantly depending on the project and client. Senior management needs improvement. Decisions can sometimes feel disconnected from the actual experience of employees working on projects. Company culture could be much better. There is a lack of consistency in how employees are treated and how career-related decisions are communicated. Compensation is below what one would expect considering the workload and market standards. Salary hikes are often disappointing and don't always reflect the employee's contribution, performance, or increased responsibilities. Promotions can be a frustrating process. In some cases, promotion decisions appear to get unnecessarily delayed by HR despite employees meeting the expected criteria and receiving positive feedback. Career growth and recognition can feel heavily dependent on the project and management you happen to be working with.
View on GlassdoorPros: -Short term projects. -Lot of learnings and again that depends upon the projects. -Good benifits and descent pay.
Cons: -Very less work life balance. -Some internal Politics
View on GlassdoorPros: Flexible hybrid work model in blr office
Cons: Not as such depends on project to project
View on GlassdoorCompany review data sourced from Glassdoor.
Glassdoor salary estimates for top hiring roles
| Role | Location | Median | Range (LPA) | Reports |
|---|---|---|---|---|
| Data Engineering Manager | India | 31.5 LPA | 25.0 LPA – 32.0 LPA | 3 |
Salary benchmarks are estimates from Glassdoor and may differ from individual job listings.
18 questions indexed · 5 role tracks
Sign in to browse all 18 questions with answer outlines, filters, and Copilot prep plans.
Questions reported by interview candidates on Glassdoor; edited for clarity. Not guaranteed to match your exact interview.
India-scoped Glassdoor interview reports · 440 total · avg difficulty 3.0/5 · 466 questions indexed
It was very easy with basic dsa in your preferred language and basic sql concepts like joins. Prepare basic dsa and sql it will help to get on interview process
Sample questions
The interview process was well-structured and moved quickly through standard analytical evaluations. It started with an initial HR screening call to discuss my background and resume details, followed by a technical assessment round focusing on SQL, data analysis logic, and problem-solving skills. The final stage was a managerial round evaluating project experience and situational fit before receiving the offer.
Sample questions
Two rounds happened with some coding questions from SQL , pyspark and some deep dive into Databricks and ADF. Asked to solve Leetcode Medium-hard SQL question. Focus on spark optimization, Databricks new features and should be able to explain the previous projects.
Sample questions
Expectations for micromanagement led to job offer rejection. I cleared round no. 1 interview. The round 2 interview was interesting as well as shocking at the same time. Please go through the following and think twice whether to join this company or not as a technical (Dev, QA) professional.
Sample questions
interviewer was very very chill, he asked a lot of questions from statistics and probability and ml dl concepts, he also gave a dsa question at the end, if u solve that u go to next round which was completely resume based and then finally hr round
Sample questions
Questions reported by interview candidates on Glassdoor; edited for clarity. Not guaranteed to match your exact interview.
Top hiring roles: Engineering
Last updated 26 October 2026
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