Srinivas A

Senior Software Engineer

Bengaluru, Karnataka, India12 yrs 4 mos experience

Highly Stable

Key Highlights

Designed scalable event-driven systems for high throughput.
Achieved 100% reliability across complex distributed systems.
Reduced infrastructure costs significantly using cloud-native solutions.

Stackforce AI infers this person is a SaaS architect specializing in high-throughput, event-driven systems.

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Skills

Core Skills

Event-driven ArchitectureCloud ArchitectureReal-time Data ProcessingEvent StreamingData ProcessingMicroservicesData Quality

Other Skills

AWSAgile MethodologiesAirflowAmazon Elastic MapReduce (EMR)Amazon S3Amazon Web Services (AWS)Analytical TechniquesApache KafkaApache SparkApache Spark StreamingAzure EventHubAzure FunctionsAzure QueuesBig DataBigQuery

About

Architect with hands-on expertise designing and scaling event-driven systems that process millions to billions of messages reliably and efficiently. I work at the intersection of real-time data, distributed computing, and high-throughput architectures — building serverless pipelines that just don’t break. ⚙️ What I focus on: • Architecting systems to handle 100K+ requests per second with auto-scaling, resiliency, and cost-efficiency. • Designing distributed, fault-tolerant event pipelines with clean separation of concerns. • Building data ingestion flows that power fast analytics and operational insights. • Optimizing across compute, messaging, caching, and storage for peak performance. I thrive on solving system bottlenecks, designing for scale, and delivering production-grade cloud architectures. Whether it’s hundreds of queues, global deployments, or fine-tuned metrics — I go deep, stay hands-on, and make it work.

Experience

12 yrs 4 mos

Total Experience

3 yrs 7 mos

Average Tenure

1 yr 5 mos

Current Experience

Microsoft

Senior Software Engineer

Jan 2025 – Present · 1 yr 5 mos · Bengaluru, Karnataka, India · Hybrid

Enterprise-Scale ACL Automation Framework
Role: Lead Architect & Developer
Technologies: Azure EventHub, Azure Functions, Azure Queues, Kafka, Kusto, Data Lake, Entra ID
Led the design and delivery of a scalable, event-driven platform to automate access control operations across billions of enterprise data assets. The solution resolved a year-long operational bottleneck, introduced robust validation, and became a reusable framework for secure, idempotent ACL workflows across distributed environments.
Designed and delivered a scalable event-driven platform for automating ACL operations across billions of enterprise data assets
Standardized ~1 billion ACLs across ~500 million files and folders with zero flaws introduced
Remediated 50,000+ Entra ID groups across multiple business units without downtime or access loss
Achieved 100% reliability across 600+ downstream systems — no SEVs, no job failures, no regressions
Completed full ACL standardization in under 3 weeks, unblocking workstreams stalled for over a year
Reduced infrastructure cost by ~80% (from ~$100K to ~$15K) using modern cloud-native architecture
Performed multi-level ACL validations using Kusto, retaining historical snapshots for rollback and audit
Engineered a reusable, idempotent framework for secure file and folder operations across data lakes
Enabled partner-led cleanup of deprecated data, reducing footprint from 1.2 billion to ~500 million files
Built with best practices for observability, concurrency, and fault tolerance — ready for multi-tenant scale

Azure EventHubAzure FunctionsAzure QueuesKafkaKustoData Lake+3

Groupon

3 roles

Software development Engineer 4

Nov 2023 – Dec 2024 · 1 yr 1 mo

Janus- Realtime Event Canonicalized Platform
Janus is a versatile and scalable platform designed to onboard events from diverse sources, including web, mobile, internal services, and queues, serving as a single source of truth for all event data. It enables clients to map raw events into canonical formats, create custom metrics and alerts on derived attributes, and access data via Kafka, BigQuery, Delta Lake, Hive, or file-based systems with batch, real-time, and near-real-time frequencies. Supporting broad use cases like data science, marketing analytics, and dashboard creation, Janus processes 1–2 billion events daily, adapting dynamically to traffic and occasions. With advanced features such as user-defined functions (UDFs) for custom translations and a robust tech stack leveraging Spark Streaming, Kafka Streams, Kubernetes, Java, and ActiveMQ, Janus ensures high performance and reliability. Its real-time observability is powered by InfluxDB and Wavefront, providing millisecond-level dashboards for tracking trends like orders, app crashes, downloads, and email clicks, driving actionable insights across the organization

Query OptimizationComputer ScienceGoogle Cloud Platform (GCP)OptimizationKubernetesData Streaming+2

Software development Engineer 3

Mar 2021 – Nov 2023 · 2 yrs 8 mos

Audience Service - Marketing-Tech
Stakeholders create different variety of Audiences and Campaigns that are used for marketing emails, push notifications, social media affiliate marketing, etc. Holds data responsible for daily 300M emails, 100M push notifications and much more.
Led and built the Audience Service system with a team of 5, serving as the backbone of the push marketing funnel. Consists of a UI platform, microservices, and a data processing layer, delivering scalable APIs handling 50k RPS for parallel reads and writes.Powers cohort delivery via Kafka, REST API, and HDFS, processing 2000+ workloads. Utilizes Java, Kubernetes, Spark, Kafka, and
Cassandra.

Query OptimizationComputer ScienceGoogle Cloud Platform (GCP)OptimizationKubernetesData Streaming+2

Software Development Engineer 2

Apr 2018 – Mar 2021 · 2 yrs 11 mos

Built aggregated consumer data system (table, API) providing simple, consistent answers to common and uncommon org questions, driving deep insight and empowering Consumer Value growin. It holds 450+ facts of 300M consumers such as predicted CV, affinity,9_block_segment.
Designed and built a multitenant microservice for third-party onbording for PI data. Key features include multithreaded large file uploads/downloads ability, GDPR data masking, auditing, scheduling, pre/post mapping rules, and idempotent retries forreads/writes. It supports multi-tenant Kubernetes deployments with interfaces like SFTP, REST API, and proxy servers. Tech stack:Java, Quartz, Redis, MySQL, HDFS.
Built a config-driven Data Quality framework integrated with InfluxDB, Visualizations, and PagerDuty. Built with Scala and Spark,currently configured for more than 1000+ DQ checks for HDFS datasets.Used by Marketing teams, it supports trend analysis, moving averages, null checks, regex validation, etc with flexible alert scheduling. Built a DSL and config is written in typesafe configfiles.

Computer ScienceGoogle Cloud Platform (GCP)OptimizationKubernetesData StreamingData Quality+1

Paypal

Senior Software Engineer (payroll Altimetrik)

Mar 2017 – Apr 2018 · 1 yr 1 mo · Chennai, Tamil Nadu, India

Optimization

Tata consultancy services

Software Engineer

Dec 2013 – Feb 2017 · 3 yrs 2 mos · Chennai, Tamil Nadu, India

Worked for banking and retail domains. World Bank, Nielsen
part of COE for bigdata systems.
Part of Nielsen cutting edge product (name can't be disclosed) core team member.
Player role for designing, brainstorming, discussing with Architects, implementing microservices APIs and Data processing layers on Data lake.
Delegated and communicated with cross teams for SDLC .
Built Java web applications in world Bank.
Built features independently which involved design, review, implementation,testing, deployment.
Followed Agile methods in the team.
Received "star of the month" award twice.
Received "innovative minds" award in COE team.
Received "spot award" .

Optimization