INTURI SUPARNA BABU

This Resume Template helped land interviews at 6+ top companies like TCS, IBM, and Varrlyn for Senior Data Engineering roles... Here’s exactly what made it stand out 👇 🔹 𝗜 𝗵𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝗲𝗱 𝗺𝘆 𝗿𝗲𝗮𝗹 𝗰𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻𝘀, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗷𝗼𝗯 𝘁𝗶𝘁𝗹𝗲𝘀  Instead of just saying “worked on Azure,” I wrote:  ✔ “Built a data pipeline on Azure that handled multi-source ingestion, transformation via Databricks (PySpark), and loaded into Synapse.”  ✔ “Reduced reporting latency by 35% through Spark optimization and staging layer tuning.” 🔹 𝗘𝘃𝗲𝗿𝘆 𝗯𝘂𝗹𝗹𝗲𝘁 𝗽𝗼𝗶𝗻𝘁 𝘀𝗵𝗼𝘄𝗲𝗱 𝗶𝗺𝗽𝗮𝗰𝘁 Recruiters don’t care what tools you know unless they see why it mattered. I used data to tell the story → cost savings, performance boosts, automation wins. 🔹 𝗜 𝘁𝗮𝗶𝗹𝗼𝗿𝗲𝗱 𝗺𝘆 𝗿𝗲𝘀𝘂𝗺𝗲 𝘁𝗼 𝗺𝗮𝘁𝗰𝗵 𝘁𝗵𝗲 𝗝𝗗 The target role needed Azure, ADF, Databricks, SQL → my resume had all of them front and center with project context. 🔹 𝗞𝗲𝗽𝘁 𝗶𝘁 𝗰𝗹𝗲𝗮𝗻, 𝗔𝗧𝗦-𝗳𝗿𝗶𝗲𝗻𝗱𝗹𝘆 & 𝗱𝗶𝗿𝗲𝗰𝘁 No colors, no graphics, only just clean formatting, focused bullet points, and keywords from real job descriptions. 🔹 𝗔𝗱𝗱𝗲𝗱 𝗰𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗵𝗮𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝗲𝗱 Microsoft Azure, Databricks Certified Associate, and Data Engineering badges from actual client projects. But let’s be real → no resume will work if you don’t have real-world experience. To truly switch into Data Engineering, you need projects that reflect enterprise-level problems: Spark tuning, Azure pipelines, scalable storage, and real DevOps collaboration. That’s why I recommend Bosscoder Academy → https://bit.ly/44IzcvW They’ve already helped 𝟮𝟮𝟬𝟬+ 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹𝘀 land top roles in Data & Cloud. Here’s what makes the difference:  💡 Full-stack Data curriculum (Azure, PySpark, ADF, SQL, Delta Lake)  💡 1:1 mentorship with engineers from FAANG & top MNCs  💡 Real projects to add in your resume not just toy datasets  💡 Resume reviews, mock interviews, job switch support #dataengineering #careertransition #resume #azuredataengineer #workingprofessionals #sponsoredpost

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2017 I have started as a #DataAnalyst in Wipro 👩🏻‍💻 2018 I got a chance to work on #DataEngineering tools there. Here is the roadmap that I have followed 𝗦𝘁𝗲𝗽 𝟭: 𝗦𝗤𝗟 - Basic SQL Syntax - DDL, DML, DCL - Joins & Subqueires - Views & Indexes - CTEs & Window Functions 𝗦𝘁𝗲𝗽 𝟮: 𝗣𝘆𝘁𝗵𝗼𝗻 - Fundamentals - Numpy - Pandas 𝗦𝘁𝗲𝗽 𝟯: 𝗣𝘆𝘀𝗽𝗮𝗿𝗸 - RDD - Dataframe - Datasets - Spark Streaming - Optimization techniques 𝗦𝘁𝗲𝗽 𝟰: 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘀𝘂𝗶𝗻𝗴/𝗗𝗮𝘁𝗮 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 - OLAP vs OLTP - Star & Snowflake Schema - Fact & Dimension Tables - Slowly Changing Dimensions (SCD) 𝗦𝘁𝗲𝗽 𝟱: 𝗖𝗹𝗼𝘂𝗱 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 - Nosql DB - Relational DB - Datawarehousing - Scheduling & Orchestration - Messaging - ETL Services - Storage Services - Data Processing Services Free resources to learn these skills. Azure Data Engineer Roadmap - https://lnkd.in/dbh8piJT Data Engineering Projects - https://lnkd.in/dQb339Ww SQL - https://lnkd.in/d4Nt7ehH Python - https://lnkd.in/dNAKAAxP __________________________________________________ I've created a recorded training program to save your time on interview preparation: https://lnkd.in/dt5qchck

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🚀 Cracking Data Engineering Interviews Just Got Easier! 🚀 I’ve compiled the complete Celebal Company L1 Interview Q&A – covering Azure Data Factory, PySpark, Databricks, SQL, Delta Lake, ADF triggers, schema drift handling, query optimization, caching vs persistence, late data handling, fact table tuning, time travel in Delta Lake, and much more! This document is a goldmine for Data Engineers, especially if you’re preparing for Celebal Company, but it also helps for interviews at PwC, Deloitte, Tata Consultancy Services, Infosys, Accenture, Capgemini, Cognizant, Wipro, EY, KPMG India, Tech Mahindra, HCLTech, and Microsoft Azure roles. 🔥 What you’ll learn inside: ✔ Azure Data Factory real-world scenarios (metadata-driven pipelines, triggers, schema drift) ✔ SQL optimization (indexes, fact table tuning, window functions, UNION vs UNION ALL) ✔ PySpark must-know coding exercises ✔ Delta Lake features (time travel, Z-ordering, schema evolution) ✔ Spark concepts (cache vs persist, checkpointing, actions vs transformations) ✔ Common interview puzzles asked in L1 rounds 💡 Whether you’re a Fresher, Junior, or Senior Data Engineer, this resource will boost your confidence and success rate in interviews. 👉 Save this post, share with friends, and get ready to crack your next Data Engineering interview like a pro! 🔑 For More Content, follow Sachin Patil #AzureDataEngineer #DataEngineering #CelebalInterview #AzureDataFactory #Databricks #PySpark #DeltaLake #SQLInterview #BigData #CloudComputing #ADFInterview #SparkOptimization #DataEngineerCareer #TechJobs #CareerGrowth #MicrosoftAzure #DataPipeline #InterviewPreparation #DataEngineerCommunity #JobSeeker #ITCareers

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𝐏𝐫𝐞𝐩𝐚𝐫𝐢𝐧𝐠 𝐟𝐨𝐫 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬? Here’s a complete collection of interview questions and answers designed for Azure, Databricks, SQL, PySpark, ADF, and Data Warehousing concepts. 🔹 Covers real-time scenario-based questions 🔹 Includes SQL challenges, pipeline design, and data validation cases 🔹 Prepares you for both technical rounds & HR discussions 🔹 Useful for roles like Data Engineer, Azure Data Engineer, Big Data Engineer, and ETL Developer This resource is tailored to help you explain concepts clearly, connect with real project experience, and confidently crack interviews at top companies. 💡 Whether you’re starting your journey or looking for your next career move, this will help you stand out in interviews and land your dream Data Engineering role. Follow me Kirolos Daniel for more resources. #DataEngineering #AzureDataEngineer #BigDataEngineering #DataEngineerInterview #SQLInterviewQuestions #PySparkInterview #AzureDatabricks #ETLDeveloper

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