Shahnawaz Mohammed
Engineering Manager at New Relic
Hyderabad, Telangana, India
Summary
🤩
Rockstar🎓
Top SchoolShahnawaz Mohammed is an engineering manager based in Hyderabad with 7 years of experience leading SRE teams and shipping Gen AI products. He combines hands-on systems engineering—demonstrated by contributions to TimescaleDB improving compressed-chunk indexing and stats—with a track record of architecting highly fault-tolerant, auto-scalable distributed platforms. His background spans technical leadership roles building microservice and distributed ledger systems, real-time transaction datastores, and performance-focused solutions using Erlang, Prometheus, and Grafana. At New Relic and prior companies he has owned feature delivery, incident response, and platform reliability while mentoring teams and driving design decisions. Notably, his practical database internals work on a popular time-series Postgres extension reveals deep expertise in production data systems beyond typical management responsibilities.
7 years of coding experience
19 years of employment as a software developer
SSC Science, SSC Science at Aligarh Muslim UniversityMCA Computer sciences, MCA Computer sciences at Motivational PathwayPGSSP Advance Computer sciences, PGSSP Advance Computer sciences at International Institute of Information Technology Hyderabad (IIITH)BCA Computer sciences, BCA Computer sciences at Chaudhary Charan Singh University
English, Hindi, Bengali
Github Skills (8)
timeseries-database10
databases10
timescaledb10
postgresql10
sql10
database10
compression9
analytics8
Programming languages (10)
Github contributions (5)
timescale/timescaledb
Oct 2022 - Oct 2022
A time-series database for high-performance real-time analytics packaged as a Postgres extension
Role in this project:
Database Engineer / Database Administrator
Database Engineer / Database AdministratorContributions:34 reviews, 1 commit, 17 PRs in 1 day
Contributions summary:Shahnawaz made several commits focused on improving TimescaleDB's functionality and resolving issues related to data compression and chunk management. They implemented index support for compressed chunks, allowing for optimization through index scans. They also addressed inconsistencies in chunk counts reported by various views and improved stats handling for uncompressed chunks, enhancing database performance and maintainability. The commits included changes to SQL files related to testing and code updates impacting database internals.
postgresql-extensionfinancial-analysiscomplex-queriestime-seriestsdb
shhnwz/timescaledb
Sep 2022 - Jan 2024
An open-source time-series SQL database optimized for fast ingest and complex queries. Packaged as a PostgreSQL extension.
Contributions:121 pushes, 16 branches in 1 year 4 months
postgresql-extensionsql-databasesqltimeseries-databasetimescaledb
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