SDE 3 - Backend (Platform)

4 Months ago • 7 Years + • Backend Development

Job Summary

Job Description

Dream11 seeks an SDE 3 - Backend (Platform) to build and optimize highly scalable data and ML platforms. Responsibilities include owning the full project lifecycle (design, architecture, development, deployment, monitoring), investigating and resolving incidents, building resilient platforms for Big Data and ML challenges, developing features in a distributed microservices environment, and mentoring engineers. The ideal candidate has 7+ years of experience in object-oriented programming (Java or Python preferred), 2+ years in designing and optimizing Big Data and ML services, and experience with AWS or GCP. The platform handles over 450 million RPM at peak with over 15 million concurrent users, utilizing technologies like Spark, Flink, Cassandra, Aerospike, Akka, VoltDB, Ignite, and Pulsar.
Must have:
  • 7+ years OOP experience (Java/Python)
  • 2+ years Big Data/ML service experience
  • AWS or GCP experience
  • Microservices architecture experience
  • Full project lifecycle ownership

Job Details

ML & Data Platform @Dream11:
Technology is at the core of everything we do. Our technology team helps us deliver a mobile-first experience across platforms (Android & iOS) while managing over 450 million RPM at peak with a user concurrency of over 15 million.
Building highly specialised and scalable data and ml platforms are key for driving excellence at this scale. Our Data and ML Platforms work with petabytes of data, and deliver the best user experience by running ML models at a scale of 60 million RPM. Data and machine learning is at the heart of driving product innovations and form a core tenet for all our decisions. Our platforms are built on a tech stack which is hosted on AWS & GCP with distributed systems like Spark, Flink, Cassandra, Aerospike, Akka, Voltdb, Ignite, Pulsar etc.

Your Role:

    • Owning the full project lifecycle, from designing and architecture to development, deployment, and monitoring
    • Investigating issues, incidents, and outages, performing root cause analysis, and preparing detailed reports
    • Building resilient, scalable platforms to solve Big Data and Machine Learning challenges efficiently
    • Developing scalable features for Data and Machine Learning in a distributed microservices environment
    • Mentoring engineers and ensuring that high standards and best practices are maintained throughout the development process

Qualifiers:

    • 7+ years of hands-on experience in any object oriented programming language, preferably Java or Python
    • 2+ years of experience in designing, building, and optimising Big Data and Machine Learning services
    • Practical experience with AWS or GCP
About Dream Sports:

Dream Sports is India’s leading sports technology company with 250 million users, housing brands such as Dream11, the world’s largest fantasy sports platform, FanCode, a premier sports content & commerce platform and DreamSetGo, a sports experiences platform.

Dream Sports is based in Mumbai and has a workforce of close to 1,000 ‘Sportans’. Founded in 2008 by Harsh Jain and Bhavit Sheth, Dream Sports’ vision is to ‘Make Sports Better’ for fans through the confluence of sports and technology.

For more information: https://dreamsports.group/

Dream11 is the world’s largest fantasy sports platform with 220 million users playing fantasy cricket, football, kabaddi, basketball, hockey, volleyball, handball, rugby, futsal, American football & baseball, on it. Dream11 is the flagship brand of Dream Sports, India’s leading Sports Technology company and has partnerships with several national & international sports bodies and cricketers.

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About The Company

Mumbai, Maharashtra, India (On-Site)

Mumbai, Maharashtra, India (On-Site)

Mumbai, Maharashtra, India (On-Site)

Mumbai, Maharashtra, India (On-Site)

Mumbai, Maharashtra, India (On-Site)

Mumbai, Maharashtra, India (On-Site)

Mumbai, Maharashtra, India (On-Site)

Mumbai, Maharashtra, India (On-Site)

Mumbai, Maharashtra, India (On-Site)

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