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Kishore Bandi
Bengaluru, India
Micro-Services, Web Services, Big Data, Design, Development, Cloud, Horizontal Scale, Data-Structures.
CodersRank Score
What is this?
This represents your current experience. It calculates by analyzing your connected repositories. By measuring your skills by your code, we are creating the ranking, so you can know how good are you comparing to another developers and what you have to improve to be better
Information on how to increase score and ranking details you can find in this blog post.
660
CodersRank Rank
Top 2%
Based on:
172 eventsTop 50
Go
Developer
India
Top 100
Protocol Buffer
Developer
India
Highest experience points: 0 points,
0 activities in the last year
Go
63.7
exp.
JSON
13.6
exp.
Python
10.1
exp.
Shell
9.6
exp.
Java
354.2
exp.
Scala
11.7
exp.
List your work history, including any contracts or internships
Skyflow Full-time
Dec 2019 - Nov 2021 (1 year 11 months)
Founding Engineer
Building Privacy Vault (We're Hiring)
Microsoft Full-time
Aug 2018 - Dec 2019 (1 year 4 months)
Engineer
o Technologies Used
C#, Azure, DocumentDB (Cosmos), ADLS, Azure Table, Spark, Hive, Yarn, SQL Server, Application Insights, PowerBI, HDInsight, Azure Active Directory, OData.
o Work
- Part of MARS(Substrate AI) Team in Office 365.
- SWSS - A Next generation (Gen 2) Extraction platform to make Customers data (Outlook Mails, Chats, Teams and
Other O365 Data) available in Compliant Fashion to Consumers.
- Reduced Data Extraction time by 50%.
- Improved Memory Utilization from Unbounded (~8GB) to Bounded 350 MB processing Millions of Users data.
- EDNE - Exchange Data .NET Extractor, Removed the older EXFS (Built on top of HDFS) and modeled a pluggable library to extract Exchange Data with Ease.
- Designed & Developed Features such as Direct Streaming & JSON-XML Streaming for processing JSON Payload's of 100's of MBs, with little to no memory overhead.
- Increased Data Completeness by 30%.
- OneBox - A Complete Testing solution which runs all required servers inside a nutshell (Inside a Single Process)
and validates any breaking change.
- Reduced Regression Build Failures to almost 0.
- Developers can run all Tests in their local with just a click of a button without the need for VM's.
- Ensured all Code Changes before Push will be validated on Cloud.
…
see more
C#, Azure, DocumentDB (Cosmos), ADLS, Azure Table, Spark, Hive, Yarn, SQL Server, Application Insights, PowerBI, HDInsight, Azure Active Directory, OData.
o Work
- Part of MARS(Substrate AI) Team in Office 365.
- SWSS - A Next generation (Gen 2) Extraction platform to make Customers data (Outlook Mails, Chats, Teams and
Other O365 Data) available in Compliant Fashion to Consumers.
- Reduced Data Extraction time by 50%.
- Improved Memory Utilization from Unbounded (~8GB) to Bounded 350 MB processing Millions of Users data.
- EDNE - Exchange Data .NET Extractor, Removed the older EXFS (Built on top of HDFS) and modeled a pluggable library to extract Exchange Data with Ease.
- Designed & Developed Features such as Direct Streaming & JSON-XML Streaming for processing JSON Payload's of 100's of MBs, with little to no memory overhead.
- Increased Data Completeness by 30%.
- OneBox - A Complete Testing solution which runs all required servers inside a nutshell (Inside a Single Process)
and validates any breaking change.
- Reduced Regression Build Failures to almost 0.
- Developers can run all Tests in their local with just a click of a button without the need for VM's.
- Ensured all Code Changes before Push will be validated on Cloud.
…
see more
Swiggy Full-time
Mar 2018 - Aug 2018 (5 months)
Software Development Engineer - IV
o Technologies Used
Scala, GoLang, Java, Apache Spark, Kafka, AWS, S3, EMR, Livy, Hive, Presto, Mesos, Zookeeper, Debezium, Kafka Connect, Kafka, Qubole, SpotInst, MySQL, Postgres, Docker, CDC, Secor, LevelDB, Prometheus, Consul, Grafana, Avro, ORC.
o Work
- Re-Designed Data platform Ingestion layer - 10 TB of data/day and 2.5 Billion Requests/Day.
- Reduced Data Availability Time from 1.45min (P95) to 500ms (P95) (Real-Time Data availability) and Increased Data Consistency to 99.99%.
- Tuned Kafka to scale 25 Billion messages/day with peak throughput of 600K/second, having 1300 topics & 10,000 partitions.
- Reduced Server costs by 75%, even when load increased almost 5x Times. System could Auto-Scale based on load.
- Designed a CDC (Change Data Capture) system to seamlessly get data in Real-Time from (Postgres and MySQL) into Data Platform system.
- Explored many other cloud technologies such as AWS, Qubole, Spotinst, GCP for Data-Platform & used technologies which were relevant.
Scala, GoLang, Java, Apache Spark, Kafka, AWS, S3, EMR, Livy, Hive, Presto, Mesos, Zookeeper, Debezium, Kafka Connect, Kafka, Qubole, SpotInst, MySQL, Postgres, Docker, CDC, Secor, LevelDB, Prometheus, Consul, Grafana, Avro, ORC.
o Work
- Re-Designed Data platform Ingestion layer - 10 TB of data/day and 2.5 Billion Requests/Day.
- Reduced Data Availability Time from 1.45min (P95) to 500ms (P95) (Real-Time Data availability) and Increased Data Consistency to 99.99%.
- Tuned Kafka to scale 25 Billion messages/day with peak throughput of 600K/second, having 1300 topics & 10,000 partitions.
- Reduced Server costs by 75%, even when load increased almost 5x Times. System could Auto-Scale based on load.
- Designed a CDC (Change Data Capture) system to seamlessly get data in Real-Time from (Postgres and MySQL) into Data Platform system.
- Explored many other cloud technologies such as AWS, Qubole, Spotinst, GCP for Data-Platform & used technologies which were relevant.