Varun Bainsla
Verified Expert in Engineering
Data Engineer and Developer
Bangalore, India
Toptal member since September 10, 2026
Varun is a data engineer with around 4 years of experience architecting and optimizing data pipelines, cloud infrastructure, and analytics solutions for clients such as VoltMoney, Nira Finance, and Srijan. His primary expertise is in AWS, GCP, and Azure for fintech and healthcare, where he thrives in building scalable data platforms. Varun achieved a 90% cost reduction and 10-minute analysis latency while at VoltMoney.
Portfolio
Experience
- AWS Lambda - 5 years
- Amazon S3 (AWS S3) - 5 years
- DMS - 5 years
- Python - 5 years
- Amazon QuickSight - 5 years
- FastAPI - 5 years
- Apache Iceberg - 3 years
Preferred Environment
AWS IoT, GCP, Azure, Docker, Git, Bitbucket, Jira, Apache Airflow, Tableau
The most amazing...
...data lakehouse I've architected achieved a 90% cost reduction and enabled real-time business insights with just 10 minutes of analysis latency.
Work Experience
Data Engineer
VoltMoney
- Architected and deployed a data lakehouse from scratch using Iceberg tables, S3, Athena, Debezium, and DMS, achieving 90% cost reduction and 10-minute analysis latency for real-time business insights.
- Automated 99% of ETL pipelines using Lambda and SNS/SQS event-driven architecture with S3 log storage, handling dynamic schema changes and new table provisioning.
- Designed and implemented QuickSight dashboards with optimized fact tables and direct query features, improving business operational efficiency by 70%.
- Prototyped and developed a RAG-based customer support system using Qdrant/pgvector, Ollama local LLM, and Claude API to streamline user onboarding workflows.
- Built a custom MCP server using Python and FastMCP framework for internal text-to-SQL analysis, eliminating stakeholder dependency on analytics teams.
- Architected an AI agent framework using Strands and AWS agent core for automated partner onboarding, IAM provisioning, and ETL pipeline maintenance.
Data Engineer
Nira Finance
- Redesigned and optimized the OLAP analytic system for enhancing performance by 80% and reducing overall cloud cost by 50% using Python, AWS Glue, S3, DynamoDB Streams, and Athena.
- Built 50+ automated ETL pipelines with CI/CD using Airflow and PySpark on EMR cluster, Debezium for CDC, and Terraform for real-time data synchronization from DynamoDB Streams to the data lake.
- Deployed and managed a PostgreSQL cluster on EC2 with 2 read replicas for migration from DynamoDB to a PostgreSQL database.
- Integrated WebEngage CDP for increasing user retention, enhancing engagement by 25% and retention rates by 15%.
- Introduced data lakehouse using Iceberg table formats, resulting in more than 90% reduction in OLAP system cost.
- Designed OLTP and OLAP data models and implemented a star schema for OLAP tables.
Data Engineer
Srijan | A Material+ Company
- Developed, deployed, and structured services on the cloud. Designed APIs for seamless interaction and integration.
- Built AWS Kinesis streaming pipelines for real-time IoT device data ingestion and subsequent analytics.
- Developed an event-driven architecture using Starlette framework, asyncio, SNS, and SQS. Reduced task processing latency by 40% and improved system scalability to handle 5x more concurrent tasks efficiently.
- Conducted unit tests, set up role-based authentication, integrated Pusher for mobile alerts, and enabled real-time alerts.
- Implemented a single-table design in DynamoDB for streamlined project restructuring and optimized data handling.
- Developed a pipeline to get real-time insight from the BSE stock server.
- Created intended behavior by making logic comply with extensive FastAPI in Python.
- Used persistent AWS S3 to save and load data, ensuring that it persists across processes.
- Collaborated on ETL tasks, maintaining data integrity and verifying pipeline stability.
- Implemented cron scheduling and optimized architecture for faster ingestion.
Experience
Koi | Psychology-backed Dating App for India
http://www.meetkoi.comI built the core compatibility engine behind Koi's 58-question psychometric assessment, which scores users across attachment style, emotional intelligence, communication, values, and relationship preferences. This powers Flips, a feature I designed to explain why 2 people are compatible in plain language rather than with a black-box score.
I also built Milo, an AI dating guide powered by AWS Bedrock and AgentCore, that helps users complete their profile, interpret compatibility insights, and generate personalized conversation starters throughout their journey on the app.
As the sole engineer, I took Koi from zero to a live beta with 3,400+ people on the waitlist across Bengaluru, Mumbai, and Delhi, owning the architecture, security, infrastructure costs, and end-to-end delivery.
Education
Bachelor's Degree in Information Technology
Baba Saheb Ambedkar Institute of Technology and Management - Faridabad, Haryana, India
Certifications
Model Context Protocol: Advanced Topics
Anthropic
Introduction to Model Context Protocol
Anthropic
Data Analytics Essentials
Cisco
AWS Knowledge: Cloud Essentials
AWS
AWS Knowledge: Architecting
AWS
Skills
Libraries/APIs
PySpark, Claude API, Asyncio, Pusher, OpenAI API
Tools
Apache Iceberg, Amazon Athena, Amazon Simple Notification Service (SNS), Amazon Simple Queue Service (SQS), Amazon QuickSight, AWS Glue, Apache Airflow, Git, Bitbucket, Jira, AWS IAM, BigQuery, Cloud Dataflow, Terraform, Tableau, Amazon CloudWatch
Languages
Python, SQL, Java, Snowflake
Frameworks
Apache Spark, AWS HA, LangGraph, Hadoop, React Native
Paradigms
Object-oriented Programming (OOP), Back-end Architecture, Model Context Protocol (MCP), ETL
Platforms
AWS Lambda, AWS IoT, Azure, Docker, Databricks, Amazon EC2, Amazon Web Services (AWS), Debezium, Ollama
Storage
Amazon S3 (AWS S3), PostgreSQL, Amazon DynamoDB, Database Management Systems (DBMS), Data Pipelines, Redshift
Other
DMS, EC2, FastAPI, GCP, Amazon RDS, Amazon Kinesis, Cloud Storage, Blob Storage, MCP Servers, AWS Open Search, RAG Systems, Data Structures, Operating Systems, Big Data Analytics, Cloud Computing, System Design, KYC/Identity Verification, Analytics, Data Analysis, Data Analytics, Complex Data Analysis, Cloud, Data Engineering, Cloud Services, Big Data, Data Warehousing, Master Data, Amazon Redshift, Data Build Tool (dbt), Qdrant, Pgvector, EMR, LangChain, Prompt Engineering, DuckDB, Computer Networks, Distributed Systems, LLM Agents, Agentic AI Systems, Dashboards, Large Language Models (LLMs), OpenAI
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