Tredence

## Tredence Data Engineer Interview Experience I interviewed for the **Data Engineer role at Tredence**. The interview process focused mainly on **DSA, SQL, DBMS, Data Engineering fundamentals, System Design, and detailed project discussion**. ### Round 1 — Coding + SQL + Technical Fundamentals The first round started with coding questions. I was asked to write code with correct syntax, including questions involving **Map/HashMap and String manipulation**. After that, the interviewer asked technical questions related to SQL and databases. Topics included: Difference between **DDL, DML, DQL, DCL and TCL** Examples of commands under each category SQL commands such as `CREATE`, `ALTER`, `DROP`, `TRUNCATE`, `INSERT`, `UPDATE`, `DELETE`, `SELECT`, `GRANT`, `REVOKE`, `COMMIT` and `ROLLBACK` Differences between commonly confused SQL commands, with examples I was then asked around **3 SQL questions**, including: Find the employee with the **highest salary** Find the employee with the **highest salary in each department** Solve a problem using **SQL Window Functions** For the SQL questions, I had to explain the logic behind the queries as well. ### Round 2 — Projects + DSA + Data Engineering + DBMS + System Design The second round was more detailed and focused heavily on my **projects and technical fundamentals**. The interviewer asked me to explain my projects in depth, including: Project architecture How different components communicate Where the data is stored How data flows through the system Algorithms used Why I selected particular technologies Dry runs Pseudocode and implementation/code I was also asked a **DSA/Graph question based on Dijkstra's Algorithm**. I had to explain the algorithm, perform a **dry run**, and discuss/write the pseudocode and implementation. There were also questions about how a large-scale application such as **YouTube works**, including: High-level architecture Where different types of data are stored How data flows through the system How different components communicate The interviewer then went into **Data Engineering fundamentals**, including: What is Data Engineering? Basic Data Engineering architecture Data pipelines Data storage Data flow ETL/ELT Batch vs. real-time processing I was also asked about **DBMS and basic System Design concepts**, including: Normalization Database design Load balancing Scalability Basic system architecture How databases interact with applications ### HR / General Discussion Towards the end, the interviewer asked some general questions about: My role in my college club My responsibilities and leadership experience My achievements Extra-curricular activities My background and interests The interviewer also asked if there was anything that had **not been discussed during the technical rounds**. ### Preparation Tips Based on my experience, I would recommend preparing: DSA** Arrays Strings HashMap/Map Basic DSA Graph algorithms *Dijkstra's Algorithm** Dry runs Writing syntactically correct code SQL** DDL, DML, DQL, DCL, TCL Joins Aggregate functions `GROUP BY` and `HAVING` Subqueries Window functions `RANK()`, `DENSE_RANK()`, `ROW_NUMBER()` Highest salary problems Highest salary per department Practical SQL queries DBMS** Keys Normalization ACID properties Transactions Indexing Joins Database design Data Engineering** ETL/ELT Data pipelines Data storage Batch vs. real-time processing Basic Data Engineering architecture System Design** Basic architecture Load balancing Scalability Database design Data flow How large-scale applications work Projects** Be prepared to explain your projects in depth. The interviewer may ask about the **architecture, database, APIs, algorithms, data flow, design decisions, challenges, and why you chose a particular technology**. Overall, the interviews were a combination of **coding + SQL + DSA + DBMS + Data Engineering + System Design + project deep dive + HR/general questions**. The interviewers focused not just on definitions but also on whether I could **explain the concepts, dry-run algorithms, and justify my technical decisions**.