Engineering | Bangalore, India | Full Time
Instart Logic is the world’s first endpoint-aware application delivery solution that makes websites and
applications fast, secure, and easy to operate. Instart Logic’s platform combines machine learning,
virtualization, and open APIs with a content delivery network (CDN) for global delivery. Using Instart
Logic, organizations like Kate Spade, Office Depot, and Washington Post can provide ultra-fast,
visually immersive and secure experiences on any device to maximize revenue, deliver superior
customer experiences, and gain competitive advantage. Instart Logic is funded by Andreessen
Horowitz, Greylock, Kleiner Perkins, Stanford, Telstra, and other notable Silicon Valley
Have You Asked Yourself:
- Is Petabyte scale data processing the problem you were hunting to solve?
- Have you always had a desire to find that needle in a gigantic digital haystack?
- Are you a compulsively data-driven geek?
- Have a desire to publish your work in leading academic journals, attend industry conferences,
- and talk about how you are powering the big data platform?
- If you answered YES to any of the above, you can start filling your look ahead buffer!
- Deep passion for coding
- Versatile enough to explore and solve problems across various facets of computer science
- Big Data Processing (MapReduce and Distributed File Systems)
- Queueing, Publish/Subscribe systems
- Realtime data pipelines
- Large-scale Query Processing
- Relational and Non Relational (NoSQL) database systems
- Scalable and Fault Tolerant Serving systems
- Machine learning
- Virtualization, Containerization and Micro Services
- Data Analytics
- Distributed computing
- Large-scale system design
We are looking for a Rockstar Engineer to help design and power our big data platform. The
responsibilities will include innovating in building out a scalable, fault tolerant big data platform that
can be leveraged for gaining deep insights for both external and internal needs.
- Maintain, manage and build out a data platform that can process petabyte scale data
- Engineer a near real-time system that can process massive amounts of data
- In-depth understanding of large-scale query processing using Hive, Pig, Presto, etc.
- Design and implement the data processing, analytics, and machine learning parts of the
- Designing, building, installing, configuring and supporting Hadoop.
- Perform analysis of vast data stores and uncover insights.