Coder pad had 4 questions. 1. React - 400 points - Todo List 2. Javascript - 300 points - finding maximum lucky children that will get lucky money, given money and number of children. 3. Problem solving (any language) - 300 points - Processing array of strings to construct object and sort them. 4. Problem solving (any language) - 300 points - Decoding the string with given list of words. I was asked to find the subset of an array of strings and return the maximum length of the subset which satisfies a said condition
Senior Data Engineer Interview Questions
2,611 senior data engineer interview questions shared by candidates
Data modeling about the business, sql question and a simple python question
Un dataset m'a été envoyé, je dois effectuer les opérations de nettoyage et faire une analyse descriptive des données sur pyspark.
Tell us one time you showed to empower someone else. Tell us one time that you have implemented something challenging at your workplace. Tell us one time you have built a trusted relationship with someone at work.
1. salary expectation 2. can u work in big company culture
Coding test and Technical Interview
SQL join and window function, spark, adf
1 What are the challenges faced by distributed system and how to resolve them in most efficient way
They asked SQL and Python questions, the questions were challenging but would have been a fair play if we were given a code playground to test our queries and then submit the final answer.
A. Core Data Engineering Concepts SQL (joins, window functions, performance tuning) Data Modeling (star vs snowflake, normalization) ETL/ELT pipelines (batch vs streaming, orchestration tools like Airflow) B. Apache Spark / PySpark Catalyst Optimizer & Tungsten Narrow vs Wide transformations Joins (broadcast, sort-merge), Skew handling AQE (Adaptive Query Execution) Partitioning, Predicate Pushdown Execution Plan (DAG → Stage → Tasks) Spark UI and Job Debugging SCD Type 2 Implementation in PySpark C. AWS S3, Glue, Athena, Lambda, EMR, Redshift Event-driven design (S3 → EventBridge → Lambda) Security: IAM roles, bucket policies, encryption CI/CD in AWS (CodePipeline, CloudFormation) D. Python Writing modular, reusable code Working with Pandas, Boto3 (for AWS interaction) Exception handling, logging Lambda functions and decorators E. Kafka / Streaming Kafka topic partitioning, consumer groups Offset management Integration with Spark Structured Streaming
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