Azure devops intermediate level questions

Below is a curated list of intermediate-level Azure DevOps questions that focus on practical knowledge, technical understanding, and scenario-based problem-solving. These questions are designed to assess a candidate’s ability to implement and manage Azure DevOps tools and processes effectively, suitable for professionals with some experience in DevOps practices. Each question includes a brief explanation or... Continue Reading →

Processing 10 TB of Data in Databricks!!

Interviewer: Let's assume you're processing 10 TB of data in Databricks. How would you configure the cluster to optimize performance?Candidate: To process 10 TB of data efficiently, I would recommend a cluster configuration with a large number of nodes and sufficient memory.First, I would estimate the number of partitions required to process the data in... Continue Reading →

PySpark Data Engineer Interview experience at Big 4

Introduction: Can you provide an overview of your experience working with PySpark and big data processing?I have extensive experience working with PySpark for big data processing, having implemented scalable ETL pipelines, performed large-scale data transformations, and optimized Spark jobs for better performance. My work includes handling structured and unstructured data, integrating PySpark with databases, and... Continue Reading →

Low Level System design articles

These articles will save you 50+ hours of hopping to resources and wasting time. 1) Scalability: https://lnkd.in/gq4hW9qx 2) Horizontal vs Vertical Scaling: https://lnkd.in/g8qcwRCy 3) Latency vs Throughput: https://lnkd.in/gDAx6QQd 4) Load Balancing: https://lnkd.in/gefSiXEJ 5) Caching: https://lnkd.in/gAp-9udf 6) ACID Transactions: https://lnkd.in/g-sjsMwX 7) SQL vs NoSQL: https://lnkd.in/gwCe58TU 8) Database Indexes: https://lnkd.in/gE_q5m_g 9) Database Sharding: https://lnkd.in/gFdNxDrU 10) Content Delivery... Continue Reading →

Cloud Services in one line

If you are an aspiring Data Engineer then you must know these cloud services w.r.t AWS or AZURE or GCP 👇 Save this post for future reference ...1️⃣ Amazon Web Services (AWS)🛠 AWS Data Pipeline: For creating complex data processing workloads.📊 AWS Glue: Our favourite fully managed ETL service.💾 Amazon S3: An object storage service... Continue Reading →

Google Cloud Compute Engine vs App Engine

Google Cloud Platform provides a wide range of computing services that target broad categories of user needs.  The Google Cloud Platform provides mainly 6 types of compute options: – App Engine Compute Engine Kubernetes Engine Cloud Functions Cloud Run VMware Engine Now let’s talk about some of these services in brief. Compute Engine The Compute... Continue Reading →

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