Dhruva Vatsa Mishra

Software Engineer

Bengaluru, Karnataka, India6 yrs 11 mos experience

Highly Stable

Key Highlights

Architected enterprise-scale infrastructure for B2B SaaS.
Delivered solutions for 15M+ users and 140+ enterprise clients.
Expertise in data platforms and ML infrastructure.

Stackforce AI infers this person is a SaaS expert with a strong focus on data platforms and machine learning infrastructure.

Contact

Skills

Core Skills

Data PlatformsMl InfrastructureDistributed SystemsMl Pipeline EngineeringMicroservicesData InfrastructureBig Data EtlSoftware Development

Other Skills

MLflowKubeflowKubernetesApache KafkaMachine LearningData EngineeringSoftware ArchitectureGraphQLRabbitMQRedisgRPCProtocol BuffersObject-Oriented Programming (OOP)MLOpsAmazon Relational Database Service (RDS)

About

I am a platform-focused engineer specialising in zero-to-production solutions with core expertise in 𝗗𝗮𝘁𝗮 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀 (petabyte-scale data lakes, real-time pipelines), 𝗠𝗟 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 (MLOps, distributed training, automated deployment), and 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 (fault-tolerant microservices, multi-tenant architecture). Over the years, I have architected enterprise-scale infrastructure for B2B SaaS organisations, delivering solutions from energy analytics platforms serving 15 M+ users to satellite-driven systems powering 140+ enterprise clients across the utility and enterprise sectors. Let's connect if you're building something extraordinary.

Experience

6 yrs 11 mos

Total Experience

3 yrs 1 mo

Average Tenure

8 mos

Current Experience

Granica

Senior Software Engineer

Oct 2025 – Present · 8 mos · Remote

Building ML-powered data compression systems to optimize petabyte-scale cloud lakehouses at Granica.

MLflowKubeflowKubernetesMicroservicesApache KafkaMachine Learning+47

Aidash

SDE 3

May 2021 – Oct 2025 · 4 yrs 5 mos · Bangalore Urban, Karnataka, India · Hybrid

𝗚𝗲𝗼𝘀𝗽𝘁𝗶𝗮𝗹 𝗖𝗹𝗼𝘂𝗱-𝗡𝗮𝘁𝗶𝘃𝗲 𝗗𝗮𝘁𝗮 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺: Architected enterprise-grade medallion data platform processing 4TB daily (1.6 B+ data points), accelerating deployment cycles by 97% (90 days → 30 minutes) and reducing infrastructure costs by 82% through optimised Airflow, Apache Iceberg, and Spark implementation
𝗠𝗟 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: Built a distributed satellite image processing system handling 2 M+ tiles, delivering 95% optimisation improvement and accelerating processing speed by 60% via asynchronous FastAPI and RabbitMQ pipelines supporting concurrent workflows
𝗗𝗮𝘁𝗮 𝗔𝗰𝗾𝘂𝗶𝘀𝗶𝘁𝗶𝗼𝗻 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸: Designed a multi-vendor satellite ingestion system across UK/US markets, reducing client onboarding from weeks to days and cutting acquisition costs by 85% while processing 5,000 sq km²/day
𝗠𝗶𝗰𝗿𝗼𝘀𝗲𝗿𝘃𝗶𝗰𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: Developed a scalable B2B platform using Java SpringBoot and Scala microservices, onboarding 20 enterprise clients within the first year through optimised geospatial PostgreSQL pipelines
𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽: Mentored 8 interns and 3 junior engineers, and drove cross-functional initiatives from POC to production deployment

PySparkJavaData PlatformsML Pipeline EngineeringMicroservices

Bidgely

2 roles

Software Engineer

Jul 2019 – May 2021 · 1 yr 10 mos · Bengaluru Area, India

𝗘𝗻𝗲𝗿𝗴𝘆 𝗗𝗮𝘁𝗮 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲: Engineered scalable AWS platform processing 1.5 B+ daily data points (150GB) from 15 M+ users, implementing Cassandra, Redshift, RDS, and Redis architecture with tenant-based traffic throttling for optimal performance
𝗥𝗮𝘁𝗲 𝗖𝗼𝗺𝗽𝗮𝗿𝗶𝘀𝗼𝗻 𝗘𝗻𝗴𝗶𝗻𝗲: Designed an innovative algorithm analysing consumption patterns across utility rate plans, delivering 2-5% customer bill savings and increasing customer satisfaction through personalised rate insights in the consumer portal
𝗕𝗶𝗴 𝗗𝗮𝘁𝗮 𝗘𝗧𝗟 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲: Developed Apache Spark-based batch pipeline moving streamed data through ETL to S3 data lake with Redshift querying, reducing infrastructure costs by 40% while maintaining data processing SLAs and establishing foundation for client Spring Boot API integration

JavaScalaData InfrastructureBig Data ETL

SDE Intern

Jan 2019 – Jul 2019 · 6 mos · Bengaluru Area, India

𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗘𝗻𝗴𝗶𝗻𝗲: Developed an intelligent recommendation system analysing user energy consumption patterns, delivering personalised actionable insights that increased customer engagement and drove energy optimisation behaviours through data-driven recommendations
𝗣𝗗𝗙 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 𝗦𝗲𝗿𝘃𝗶𝗰𝗲: Enhanced enterprise PDF validation service with configurable text and image validation rules, ensuring 100% compliance with customer delivery standards and reducing manual review overhead by implementing automated quality control pipelines

JavaSpring FrameworkSoftware Development