Lavi Singla

CTO

Gurugram, Haryana, India4 yrs 11 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in database optimization and cost reduction strategies.
Proficient in Agile methodologies and REST API development.
Strong background in machine learning and data modeling.

Stackforce AI infers this person is a Fintech professional with strong expertise in database management and optimization.

Contact

Skills

Core Skills

Database ManagementSql OptimizationCache ManagementPerformance OptimizationApi Development

Other Skills

API AnalysisAgile EnvironmentAlgorithmsAmazon Web Services (AWS)AngularAngular MaterialAngularJSData ModelingData StructuresDatabase Management System (DBMS)Database OptimizationDebuggingDesign PatternsExpress.jsFlask

About

Our team at Arcesium has executed strategic database optimizations, enhancing product satisfaction through intelligent resource management. This included reducing peak database CPU usage, a crucial step in cutting server costs, and refining SQL queries and schemas. As a Senior Software Engineer, my role extends beyond technical prowess to include a commitment to Agile methodologies and REST API development. With a solid educational foundation from PEC University of Technology, where I earned my BTech in Computer Science, my focus now is to advance the robustness of our security master platform. It's an ecosystem designed to accommodate an expansive range of over 800 asset classes, aiming to elevate client experiences and operational efficiency within the dynamic landscape of software engineering.

Experience

4 yrs 11 mos

Total Experience

4 yrs 11 mos

Average Tenure

4 yrs 11 mos

Current Experience

Arcesium

3 roles

Lead Engineer

Jul 2025 – Present · 10 mos

Senior Software Engineer

Promoted

Jan 2023 – Jul 2025 · 2 yrs 6 mos

As part of security master team, I worked on several optimization and client R&D tasks that were required for cost reduction and increasing product satisfaction from clients.
Some of the keys projects included:
1. Working on Database CPU utilization reduction to reduce DB server cost by downsizing them. To achieve this I worked on projects like optimizing sql queries, increase cache-hit ratio, analyzing existing client API usage to propose better API utilization by clients, optimizing sql schemas and indexes etc. This was all done with the target to reduce peak DB CPU usage to safely downsize db servers.
2. Analyzed usage of new cache frameworks like Hazelcast to distribute cache across multiple servers and reduce in memory server heap requirements. We were able to increase cache size by 4 times and reduce dependency of db to fulfil sql queries which can be done by cache.
3. Scaling and optimizating key scheduled jobs in security master that were SLO bounded. These jobs were earlier highly unoptimized and could even take a day to run a single job. Using graphs and hierarchy knowledge, I was able to optimize these task to run in less than 5 minutes and less than 1 hour in worst case for high input sizes. This provided cost benefits on compute cost as well.
4. Worked on several miscellenous projects that were key for client satisfaction and keeping security master in sync with latest trends. This included stabilizing arcesium client sdks etc.

Database OptimizationSQLCache ManagementAPI AnalysisJob SchedulingDatabase Management+1

Software Engineer

Jun 2021 – Jan 2023 · 1 yr 7 mos

Working as a part of Security Master team responsible for managing complete database of securities traded by different hedge funds and other investment firms.
Security master's robust data model is designed to cover over 800 different asset and sub-asset classes, including crypto assets, with more than 3,000 unique fields.

Labellerr, making ai journey easier

Software Engineer Intern

Aug 2020 – Apr 2021 · 8 mos · India

Worked as a full stack developer responsible for handling complete platform wide development.
I was responsible for handling the design and implementation of many backend critical services for the platform including:
files reader and writer APIs
cloud connectors like AWS S3, Google cloud storage, dropbox storage etc
authentication via Gmail
client dataset storage
gold standard annotation support
labelling activity management
labelled data export management etc.
Apart from these, I contributes towards many frontend screens which were integrated with above APIs to complete the backend and frontend flow.
I got in-depth knowledge of complete data modelling for all data types for annotation and understanding the complete product life cycle.

Arcesium

Summer Intern

May 2020 – Jun 2020 · 1 mo · Hyderabad, Telangana

I was working as an Intern in the Transaction and Reference Data team which manages the different types of Financial Assets and transactions and provides micro-services on top of it to entire platform to cater this data.
I worked on onboarding the temporal APIs for position and transaction readers onto the pagination framework. These APIs are used heavily by clients with requests counting to millions per day.
Got in depth knowledge of data modelling and temporal and bi-temporal data storage and handling large API loads onto server.

Eduwaive foundation

Software Engineer Intern

Jan 2020 – Apr 2020 · 3 mos · Chandigarh

During my internship at Eduwaive Foundation , I worked on one of the product of the organization called Labellerr. Labellerr is an annotation automation tool that uses Machine learning and advanced AI techniques the automate the hectic annotation process.
I was involved in working on analyzing and implementing different supervised and unsupervised machine learning models to automatically predict annotation labels for text and image data types.
I was responsible for building the complete UI to annotate text data type and integrate it with backend to store the annotated labels and automatically suggest labels for text files.
Google cloud platform was the major cloud service provider being used at Labellerr, so I got the chance to understand the complete lifecycle of deploying the backend APIs and frontend app on google compute services and using it's various managed ML APIs like image processing, speech-to-text conversion APIs etc.