‼️ Amazon is Hiring for Data Engineers ‼️ 🙋🏻 Link to apply : https://lnkd.in/g9xtKgbk 📚👨🏻🎓 ** Learn these to become an outstanding Data Engineer ** 👷🏼♂️: 1. Actual spark architecture understanding ( not just Databricks, but what happens under the hood ) 2. DE with software engineering : DE is a lot like Software development. Testing, CI/CD etc must be a norm not an option. 3. Willingness to learn : it's important to highlight this quality. We look for people who are happy to discuss a problem even if they don't completely understand the tech behind it. 4. Fundamentals of data engineering: things like data validation, consistency, creating I idempotent pipelines. ** Check out my topmate profile for Data Engineering learning resources ** #hiring #data #dataEngineer
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‼️ Amazon is hiring for Data Engineer ‼️ Link to apply : https://lnkd.in/gPfs768v Junior Data Engineer Expectations : 1. Mid level at Data Structures & Algorithms. 📊 2. In data structures and Algorithms: Good at string, array, data retrieval - like problems (Binary search) 🧩 3. Knowledge of advanced SQL 📚 4. Can write code with Spark ⚡ 5. Experience with airflow/cron jobs 🔄⏰ 6. Python or scala understanding 🐍🔄 7. Basic experience with cloud services ☁️ 8. Data engineering system design (Batch) 🛠️ Nice to have: 1. Data engineering system design (Streaming) 🌊 2. Basic knowledge of Kafka 🔄📊 3. Data warehousing knowledge 🏢 4. NoSQL Databases 📄 5. Writing test cases ✅ Follow Nitesh Chaudhry for more on Data ! #data #dataEngineering #hiring
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‼️ Amazon is Hiring for Data Engineering roles !! 🙋🏻♂️ Link to apply : https://lnkd.in/gNbCq3z6 𝐉𝐮𝐧𝐢𝐨𝐫 𝐚𝐧𝐝 𝐬𝐞𝐧𝐢𝐨𝐫 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐄𝐱𝐩𝐞𝐜𝐭𝐚𝐭𝐢𝐨𝐧𝐬 : 𝐓𝐡𝐞 𝐛𝐚𝐬𝐢𝐜𝐬: 1. Mid level at Data Structures & Algorithms. 📊 2. In data structures and Algorithms: Good at string, array, data retrieval - like problems (Binary search) 🧩 3. Knowledge of advanced SQL 📚 4. Can write code with Spark ⚡ 5. Experience with airflow/cron jobs 🔄⏰ 6. Python or scala understanding 🐍🔄 7. Basic experience with cloud services ☁️ 8. Data engineering system design (Batch) 🛠️ 𝐍𝐢𝐜𝐞 𝐭𝐨 𝐡𝐚𝐯𝐞: 1. Data engineering system design (Streaming) 🌊 2. Basic knowledge of Kafka 🔄📊 3. Data warehousing knowledge 🏢 4. NoSQL Databases 📄 5. Writing test cases ✅ Checkout my profile for Data Engineering learning content !! #hiring #data #dataEngineering
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‼️ Amazon is Hiring for Data Engineer ‼️ 🙋🏻 Link to apply : https://lnkd.in/gswjvqS7 Expectations from a junior Data Engineer : The basics: 1. Mid level at Data Structures 📊 2. In data structures and Algorithms: Good at string, array, data retrieval - like problems (Binary search) 🧩 3. Knowledge of advanced SQL 📚 4. Can write code with Spark ⚡ 5. Experience with airflow/cron jobs 🔄⏰ 6. Python or scala understanding 🐍🔄 7. Basic experience with cloud services ☁️ 8. Data engineering system design (Batch) 🛠️ Nice to have: 1. Data engineering system design (Streaming) 🌊 2. Basic knowledge of Kafka 🔄📊 3. Data warehousing knowledge 🏢 4. NoSQL Databases 📄 5. Writing test cases ✅ Need help in free Data Engineering interview content ? Check out my website in profile !! Follow Nitesh Chaudhry #hiring #data #dataEngineer
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‼ Amazon is hiring for Data Engineers ‼ 👨🎓 Link to apply : https://lnkd.in/g3twGx4G 👨💻 Topics to cover to become a spark expert : 1. Spark Submit and Important Options 2. Deploy Modes - Client and Cluster mode 3. Spark Jobs - Stage, Shuffle, Task, Slots 4. Spark SQL Engine and Query Planning 5. Spark Memory Allocation 6. Spark Memory Management 7. Spark Adaptive Query Execution 8. Spark AQE Dynamic Join Optimization 9. Handling Data Skew in Spark Joins 10. Spark Dynamic Partition Pruning 11. Data Caching in Spark 12. Repartition and Coalesce 13. DataFrame Hints 14. Broadcast Variables 15. Accumulators 16. Speculative Execution 17. Dynamic Resource Allocation 18. Spark Schedulers 19. Unit Testing in Spark To get REAL interview questions from FAANG, preparation materials, all in a single place , with 1:1 doubt clearance & Priority DM; I suggest you to check out "my website" button. #data #dataEngineering #hiring
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‼️ Amazon is Hiring for Data Engineer. 🙋🏻 Link to apply : https://lnkd.in/gswjvqS7 Expectations from a junior Data Engineer : The basics: 1. Mid level at Data Structures 📊 2. In data structures and Algorithms: Good at string, array, data retrieval - like problems (Binary search) 🧩 3. Knowledge of advanced SQL 📚 4. Can write code with Spark ⚡ 5. Experience with airflow/cron jobs 🔄⏰ 6. Python or scala understanding 🐍🔄 7. Basic experience with cloud services ☁️ 8. Data engineering system design (Batch) 🛠️ Nice to have: 1. Data engineering system design (Streaming) 🌊 2. Basic knowledge of Kafka 🔄📊 3. Data warehousing knowledge 🏢 4. NoSQL Databases 📄 5. Writing test cases ✅ Need help in cracking Data Engineering interviews ? Check out my website in profile !! Follow Nitesh Chaudhry
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‼️ Amazon is Hiring for Data Engineer. 🙋🏻 Link to apply : https://lnkd.in/gqyuJZ4R The basics: 1. Mid level at Data Structures 📊 2. In data structures and Algorithms: Good at string, array, data retrieval - like problems (Binary search) 🧩 3. Knowledge of advanced SQL 📚 4. Can write code with Spark ⚡ 5. Experience with airflow/cron jobs 🔄⏰ 6. Python or scala understanding 🐍🔄 7. Basic experience with cloud services ☁️ 8. Data engineering system design (Batch) 🛠️ Nice to have: 1. Data engineering system design (Streaming) 🌊 2. Basic knowledge of Kafka 🔄📊 3. Data warehousing knowledge 🏢 4. NoSQL Databases 📄 5. Writing test cases ✅ Need help in learning Data Engineering concepts ? Check out my topmate profile !! Follow Nitesh Chaudhry
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Hello Connections!! We are Hiring for GCP Data Engineer Position :- Data Engineer Experience :- 3-5 years Notice period :- Immediate (or) 15 Days. JOB TYPE- REMOTE/Hybrid RESPONSIBILITIES AND QUALIFICATION - Design, build, and manage data pipelines and ETL processes using GCP services like Dataflow, Dataproc, and Pub/Sub. - Optimize data processing workflows for performance, reliability, and scalability. - Ensure data quality, consistency, and accuracy throughout the data lifecycle. - Architect and manage databases on GCP, such as Cloud SQL, Bigtable, and Firestore. - Implement data partitioning, sharding, and indexing strategies for optimal database performance. - Utilize GCP's storage services like Cloud Storage and BigQuery for efficient data storage and analysis. If you are Interested Drop your Updated CV to hr@keensontech.com #gcp #aws #azure #cloud #cloudcomputing #googlecloud #devops #technology #kubernetes #python #java #google #machinelearning #covid #it #programming #clinicalresearch #javascript #tech #datascience #software #d #bigdata #coding #persikkediri #linux #neurology #metaanalysis #amazonwebservices #gbp
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‼️ Walmart Global Tech is Hiring for Data Engineer ‼️ Link to apply : https://lnkd.in/dR_Z8cNf 🙋🏻 𝐅𝐀𝐀𝐍𝐆+ 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐑𝐨𝐚𝐝𝐦𝐚𝐩 𝐟𝐨𝐫 2024: 🚀 STEP 1: The Basics: 1. 📚 Learn SQL: SELECT, FROM, WHERE, GROUP BY, JOIN, HAVING, etc 2. 🐍 Learn Python: Learn data structures and algorithms: array, dictionaries, recursion, string & array manipulation, loops. 3. 🔥 Learn Pyspark: Functions like sparkSession, Read, filter, groupBy. STEP 2: Intermediate : 1. 🌪️ Learn Airflow 2. 🛢️ Learn data lake architecture & concepts. 3. 🌟 Advanced SQL: Window functions, CTEs, Nested queries, Solving SQL problems using self-joins. STEP 3: Advanced : 1. 🚀 Learn data modelling techniques: one big table vs kimball vs Inmon vs data vault techniques 2. 🧠 Understand spark architecture: How Spark does the processing in a scalable manner. 3. Spark optimization: Predicate Pushdown, partitioning, broadcast, cache&persist, shuffle, Parallelism, Repartition&Coalesce You can use the "Save post" option for later reference. 🌐 Do visit my medium blog for a detailed roadmap!! 🔗 Follow Nitesh Chaudhry for more data-focused content !! #hiring #data #dataEngineering
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‼️ Amazon is Hiring for Data Engineer ‼️ Link to apply : https://lnkd.in/g8CH2VgQ 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐑𝐨𝐚𝐝𝐦𝐚𝐩 𝐟𝐨𝐫 2024: 🚀 STEP 1: The Basics: 1. 📚 Learn #SQL: SELECT, FROM, WHERE, GROUP BY, JOIN, HAVING, etc 2. 🐍 Learn #Python: Learn data structures and algorithms: array, dictionaries, recursion, string & array manipulation, loops. 3. 🔥 Learn #Pyspark: Functions like sparkSession, Read, filter, groupBy. STEP 2: Intermediate : 1. 🌪️ Learn #Airflow 2. 🛢️ Learn data lake architecture & concepts. 3. 🌟 Advanced SQL: Window functions, CTEs, Nested queries, Solving SQL problems using self-joins. STEP 3: Advanced : 1. 🚀 Learn #data #modelling techniques: one big table vs kimball vs Inmon vs data vault techniques 2. 🧠 Understand #spark architecture: How Spark does the processing in a scalable manner. 3. #Spark optimization: Predicate Pushdown, partitioning, broadcast, cache&persist, shuffle, Parallelism, Repartition&Coalesce I know this can be too much to grasp at a time. You can use the "Save post" option for easy reference. 🌐 Do visit my medium blog for a detailed roadmap!! 🔗 Follow: Nitesh Chaudhry #dataEngineer #dataScience #softwareEngineering
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👨💻 Amazon is Hiring for Data Roles ❗ ❗ 🙋♂️ Link to Apply : https://lnkd.in/gihc6-Nn 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐑𝐨𝐚𝐝𝐦𝐚𝐩 𝐟𝐨𝐫 2024: 🚀 STEP 1: The Basics: 1. 📚 Learn #SQL: SELECT, FROM, WHERE, GROUP BY, JOIN, HAVING, etc 2. 🐍 Learn #Python: Learn data structures and algorithms: array, dictionaries, recursion, string & array manipulation, loops. 3. 🔥 Learn #Pyspark: Functions like sparkSession, Read, filter, groupBy. STEP 2: Intermediate : 1. 🌪️ Learn #Airflow 2. 🛢️ Learn #data #lake architecture & concepts. 3. 🌟 Advanced SQL: Window functions, CTEs, Nested queries, Solving SQL problems using self-joins. STEP 3: Advanced : 1. 🚀 Learn #data #modelling techniques: one big table vs kimball vs Inmon vs data vault techniques 2. 🧠 Understand #spark architecture: How Spark does the processing in a scalable manner. 3. #Spark optimization: Predicate Pushdown, partitioning, broadcast, cache&persist, shuffle, Parallelism, Repartition&Coalesce If it is too much to grasp at a time. You can use the "Save post" option on linkedIn for easy reference. 🌐 Do visit my website for a FREE roadmap & FAANG Data Engineering Learning content. 🔗 Follow if you Like learning about data : Nitesh Chaudhry #dataEngineer #dataScience #softwareEngineering
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Senior Data Engineer at Capital Group specializing in Data Engineering
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