Saravanan Arumugam

Software Engineer

Sunnyvale, California, United States10 yrs 8 mos experience

Highly Stable

Key Highlights

Stackforce AI infers this person is a SaaS Infrastructure Engineer with a focus on data systems and user experience.

Big DataDistributed SystemsData InfrastructureUser Experience

AerospikeApache PigApache StormCC#C++ContainerizationData Processing PipelinesDatabasesDropwizardHBaseHDFSHigh Availability (HA)KubernetesLinux

Interested in building and operating data infra systems.

5 roles

Oct 2023 – Dec 2025 · 2 yrs 2 mos

I am part of a team that work on query engines. We offer Trino as a service to the entire LinkedIn. Our team contributes to open source Trino wherever its appropriate.

DatabasesBig DataDistributed SystemsKubernetesHigh Availability (HA)

Promoted

Oct 2021 – Sep 2023 · 1 yr 11 mos

I am part of the Data infrastructure group at LinkedIn. We build online, nearline, and offline infrastructure systems/tools that are used to build LinkedIn products. My contributions are mostly to the offline infra: workflow orchestration component. we have an in-house system called Azkaban, we have airflow for newer use-cases and we are currently evaluating Flyte for ML workloads.

Dec 2019 – Sep 2021 · 1 yr 9 mos

I was part of a data orchestration team in India. This was my first introduction to data infrastructure and contributing to the open source software systems.

Data InfrastructureDistributed Systems

Feb 2019 – Nov 2019 · 9 mos

I was part of the LinkedIn Lite team. The team focuses on delivering ultra low latency pages to mobile web users. Worked on delivering appropriate sized images to the users based on their network capability.

Apr 2017 – Jan 2019 · 1 yr 9 mos

India Growth team: Our team focused on improving the growth of India and emerging market LinkedIn members. This problem space is unique as it involves coming up with ideas and experimenting the same by working on many systems at LinkedIn.
what did I do?
worked on multiple experiments including how do we improve profile details of members, better on-boarding experience, connections growth through cohorted pymk recommendations.
what did I learn?
online, near-line, offline and experimentation systems at much closer look
Client ecosystem - android app, and mobile web at the beginner level

Nov 2014 – Mar 2017 · 2 yrs 4 mos · Bangalore

I was part of recommendations system in Flipkart. We served product based and personalized recommendations.
What had i been doing?
Developing and maintaining the serving layer that sends product and user based recommendations in Flipkart
Developed personalised recommendation APIs that sends content in flipkart home page
Scaled serving layer, database, and cache
What did i learn?
I learnt how do we in general solve this recommendations problem - the classical algorithms collaborative and content filtering
Got exposure to learn computation frameworks - storm and hadoop which do nearline, offline heavy lifting
Got exposure to NoSQL dbs and learnt about Redis, Aerospike, Hbase - we're using these databases in our production systems
Got exposure to build, develop and maintain micro services that are in user-path which require low latency.