Sagar Deshmukh

Director of Engineering

Pune, Maharashtra, India16 yrs 4 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Proven leadership in scaling SaaS platforms.
Expertise in microservices and cloud architecture.
Strong background in data engineering and analytics.

Stackforce AI infers this person is a SaaS-focused Engineering Manager with expertise in cloud and data engineering.

Contact

Skills

Core Skills

Amazon Web Services (aws)MicroservicesGoogle Cloud Platform (gcp)Data Warehousing

Other Skills

LeadershipJavaSoftware as a Service (SaaS)Distributed SystemsAmazon S3AWS LambdaGoogle BigQueryDatalakeTeam LeadershipPython (Programming Language)Apache AirflowExtract, Transform, Load (ETL)Apache KafkaSpring BootJenkins

About

Experienced Engineering Manager with a demonstrated history of working in the fast paced growth environments. Skilled in Java, AWS, GCP, Microservices, Python, Big Data, DevOps and distributed computing. Strong engineering professional with a Master of Business Administration (M.B.A.) in General studies from Symbiosis Institute of Business Management.

Experience

16 yrs 4 mos

Total Experience

2 yrs

Average Tenure

3 yrs 6 mos

Current Experience

Atlassian

Engineering Manager

Nov 2022 – Present · 3 yrs 6 mos · India · Remote

Chargebee

Senior Engineering Manager

Jan 2022 – Sep 2022 · 8 mos · India

Chargebee is world's leading subscription billing and revenue management SaaS platform. I am leading the core API group that handles Invoices & Taxes. Currently trying to solve scalability and performance challenges of the system that server millions of requests everyday.

Amazon Web Services (AWS)MicroservicesLeadershipJavaSoftware as a Service (SaaS)Distributed Systems+2

Uplight

Senior Engineering Manager

Oct 2020 – Dec 2021 · 1 yr 2 mos

I was working as Senior Data Engineering Manager. I have led the efforts to build an enterprise data platform to acquire, transform and analyse gigabytes of data everyday from multiple data sources. The overall size of compressed data in the datalake was in few terabytes.

MicroservicesGoogle Cloud Platform (GCP)Google BigQueryDatalakeData WarehousingTeam Leadership+4