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      Colloqui di BlackstrawColloqui per Data Engineer presso BlackstrawColloquio di Blackstraw


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      Colloquio per Data Engineer

      5 mag 2026
      Candidato anonimo a colloquio
      Pallāvaram

      Altre recensioni di colloqui per Data Engineer presso Blackstraw

      Colloquio per Data Engineer

      7 apr 2026
      Candidato anonimo a colloquio
      New York, NY
      Nessuna offerta
      Esperienza negativa
      Nessuna offerta
      Esperienza positiva
      Colloquio facile

      Candidatura

      Ho presentato la mia candidatura di persona. Ho sostenuto un colloquio presso Blackstraw (Pallāvaram) nel mese di apr 2026

      Colloquio

      I attended a walk‑in interview at BlackStraw. The process had three rounds: Round 1 – HR Intro Self‑introduction. Questions from my resume. Reason for leaving previous company. Do you have any other offers? Round 2 – Technical Round Self‑introduction. What is SCD (Slowly Changing Dimension) and its types? Which type of join would you use if one table is large and the other is small? How will you increase the performance of a query in SQL or PySpark? Difference between repartition and coalesce in PySpark. What is incremental data loading? How do you implement incremental data loading? What are the types of transformers? Difference between view and materialized view Round 3 – Managerial HR Round Self‑introduction. General discussion about background, expectations, and cultural fit. Do you have any other offers?

      Domande di colloquio [1]

      Domanda 1

      Round 1 – HR Intro Self‑introduction. Questions from my resume. Reason for leaving previous company. Do you have any other offers? Round 2 – Technical Round Self‑introduction. What is SCD (Slowly Changing Dimension) and its types? Which type of join would you use if one table is large and the other is small? How will you increase the performance of a query in SQL or PySpark? Difference between repartition and coalesce in PySpark. What is incremental data loading? How do you implement incremental data loading? What are the types of transformers? Difference between view and materialized view Round 3 – Managerial HR Round Self‑introduction. General discussion about background, expectations, and cultural fit. Do you have any other offers?
      Rispondi alla domanda
      1
      Colloquio facile

      Candidatura

      Ho presentato la mia candidatura tramite un'altra fonte. La procedura ha richiesto 3 settimane. Ho sostenuto un colloquio presso Blackstraw (New York, NY) nel mese di mar 2026

      Colloquio

      1) Recruiter Call - 10 minutes recruiter discussion about role 2) Technical Interview - 30 minutes Technical discussion based on Resume , Pyspark, Databricks 3) HR discussion - 30 minutes the interviewer was 10 minutes Late

      Colloquio per Data Engineer

      8 gen 2025
      Candidato anonimo a colloquio
      Chennai
      Nessuna offerta
      Esperienza positiva
      Colloquio difficile

      Candidatura

      Ho presentato la mia candidatura online. Ho sostenuto un colloquio presso Blackstraw (Chennai) nel mese di dic 2024

      Colloquio

      First Round was taken by HR. He asked me few questions about myself, project and asked a couple of technical questions as an initial screening. It was followed by 2 technical rounds. HR : M*h*rz*d Technical1: S**t** Technical2: M*h*m*d D*w**d*

      Domande di colloquio [1]

      Domanda 1

      1. What are the differences between snowflake schema and star schema? 2. Get the nth highest salary in each department from employee table. Was asked to write the sol in both SQL and PySpark 3. Write the python program for fibonacci series 4. What happens when you submit a job to spark ? 5. What is DAG? 6. What is the difference between Stages & Task in spark? 7. Can Stage and Task run in parallel? 8. Identify whether the given operations [select, filter, join, group by] are transformation or action ? 9. How do you implement incremental data loading? 10. Given 2 tables, each table has single column ID, get the values that are present in table B but not in table A. tableA [ ID : 1 2 3 4 5] tableB [ ID : 4 5 6 7] Expected Output : [6 7] 11. Pyspark coding question on split and explode functions.
      Rispondi alla domanda
      2