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Our Purpose and Challenges
With over 47% market-share, MakeMyTrip is India’s first and biggest travel company. In fact, one in every four passengers at an airport is our customer. Driven by the desire to provide an exceptional travel experience for our customers, we have continuously stayed ahead of the curve by developing technology and products to meet the ever-changing demands of the rapidly evolving travel ecosystem.
We are currently solving multiple challenging problems, including -
- How to bring the next 100 million users to our platform?
- How to leverage customer insights to create a truly personalised experience for users?
- How to create a delightful experience for our users, to make travel synonymous to MMT?
About the opportunity
SPARK STREAMING || KAFKA || NOSQL|| SCALA/JAVA || MONGO DB / HDFS / HBASE
What you’ll be doing
- You accurately estimate and implement machine learning models on 1.8 TB of data volume generated every day
- You will build pipelines for feature engineering by integrating data from different data sources.
- You’ll meticulously develop and deploy production data pipelines (batch + real time).
- You architect and design scalable data services that are consumed by millions of users.
- You will skillfully implement performance engineering of big data systems.
What you’ll bring to the team:
- You’ll bring the compulsory and essential experience of working with distributed systems software development.
- You’ll bring demonstrated experience of production experience in big data infrastructure and data modeling.
- You’ll bring critical experience performance optimization for both data loading and data retrieval.
- You have know-how of Spark/Kafka.
- You have invaluable knowledge in AWS Deployment, Docker and Kubernetes.
Interview Process & Prep Notes
- Basic Coding,Spark,Kafka,MySQL,Streaming,Cassandra
- You should be very well versed in building and designing large scale applications; end-to-end. Understand the pros and - cons of using relational and noSQL databases. Know how to design effective pipelines for both batch and streaming use cases.
Data Structure And Problem Solving
- Array,LinkedList, Stack, Binary Tree, Hash Tables, Heap
- Like every invention has a necessity, engineering at MMT also has one. Data structures and Algorithms have stood the test of time and have helped us solve our daily engineering problems. Binary Tree,Linked List, Algorithm Design, Dynamic Programming,Graphs are our best friends.
- Coding Assessment, Data Ingestion And Processing
- An effective data ingestion process begins by prioritizing data sources, validating individual files and routing data items to the correct destination.Your experience in data engineering is crucial for this round. Be prepared to answer some simulation-based questions during our interviews. From system design for an e-commerce platform to component interaction.
- Behavioural Assessment, Culture Fit, Project Knowledge, Role Operation
- Be yourself. It works out better for everyone if we’re genuine and can see if we’re a cultural fit for each other. Everyone here is focused on our mission, so you should figure out what it is.