Ashish Malgawa

Software Engineer

Bengaluru, Karnataka, India6 yrs 9 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Led multi-cloud architecture for Tableflow product.
Achieved zero-incident rollout of RBAC across 200+ clusters.
Developed resilient microservices and machine learning platforms.

Stackforce AI infers this person is a SaaS-focused Software Engineer with expertise in cloud architecture and microservices.

Contact

amalgawa@confluent.io LinkedIn

Skills

Core Skills

Cloud ArchitectureSoftware DevelopmentProject ManagementMachine Learning

Other Skills

ARM ArchitectureAWSAirflowAngularJSApache KafkaApache SparkAzureC++DatadogDeep LearningDockerGCPGo (Programming Language)Information RetrievalJava

About

Experienced Software Engineer with a demonstrated history of working in the computer software industry. Strong engineering professional with a Master of Technology focused in Computer Science from Indian Institute of Technology, Kharagpur.

Experience

Confluent

2 roles

Senior Software Engineer 2

Promoted

Jan 2023 – Present · 3 yrs 2 mos · Bangalore Urban, Karnataka, India · Hybrid

Founding engineer for Tableflow, owning the storage‑layer architecture for a multi‑tenant, multi‑cloud lakehouse product.
Led Tableflow’s expansion to Microsoft Azure from design through EA and GA—designing storage, identity (Workload Identity, Entra ID, provider integrations), and networking, including Azure Private Link (custom DNS and private connectivity), and leading execution, end‑to‑end validation, and GA readiness across 10+ teams.
Leading the design and early implementation of GCP support for Tableflow, extending the multi‑cloud architecture beyond AWS and Azure and aligning patterns for storage, identity, and private networking.
Previously co‑led Region Selection and led AuthN/RBAC/OAuth for Stream Governance, delivering a 9‑month roadmap and a zero‑incident GA rollout of RBAC across 200+ clusters.
Took ownership of legacy orchestrator code in Stream Governance, fixed security issues, and introduced a Jira‑driven planning culture with clear project plans, ownership, and predictable delivery.
In Marketplace Services, overhauled observability across seven services using OpenTelemetry, Datadog, and New Relic, and defined SLOs and KPIs to improve reliability and accountability.
Led the migration of 20k+ Connect clusters from x86 to ARM‑based Graviton machines, improving fleet‑wide performance and cost efficiency.

Apache KafkaKubernetesAzureGCPOpenTelemetryDatadog+3

Senior Software Engineer

Aug 2021 – Jan 2023 · 1 yr 5 mos · Bangalore Urban, Karnataka, India · Hybrid

Co-Led the Region Selection Project for Stream Governance, empowering customers to orchestrate clusters in specific
regions like AWS us-west-2.
Led the engineering initiative for AuthN, RBAC, and OAuth in Stream Governance.
Successfully managed both the Region Selection Project and the AuthN initiative, mitigating cross-team dependencies
and ensuring efficient project delivery.
Acted as a scrum master, and started a new culture of Jira Project Plans for projects in the team.
Assumed ownership of legacy orchestrator code, identifying and resolving security vulnerabilities.
Developed a comprehensive, 9-month roadmap for delivering RBAC across multiple Stream Governance products.
Achieved a flawless rollout of RBAC across 200+ Stream Governance clusters, with zero incidents or escalations during
general availability.

Apache KafkaRBACOAuthJiraSoftware DevelopmentProject Management

Appdynamics

Software Engineer

Jul 2019 – Aug 2021 · 2 yrs 1 mo · Bangalore

Re-engineered The Metrics processor microservice to make it more resilient.
Developed an algorithm to solve Head of Line blocking in Kafka.
Created ML Platform. Took ownership of multiple components, and got a special recognition award for the same.
Dockerized Kafka connect with custom SMTs, and converters to create horizontally scalable Kubernetes services.
Tuned various JVM and GC parameters to reduce the memory footprint of Kafka Connect from almost 50 GB to 10 GB.
Modified the open-source Kafka connect converter to reduce the size of ingested data at the beginning of the pipeline.
Created Spark compaction jobs to convert the Avro data to Parquet, and took advantage of its column-based compression which reduced the output size from 20 GB to 1 GB.
Created CI/CD pipeline using Airflow and Teamcity to automatically deploy spark jobs on AWS ECR.
Created Kafka Config Manager to upsert Kafka configuration changes on the fly using Kubernetes deployment.
Authored code fixes and enhancements on other ongoing projects for inclusion in future code releases and patches.
Investigated and solved several on call issues.

KafkaMachine LearningDockerKubernetesAirflowSoftware Development

Ibm

Extreme Blue Intern

May 2018 – Jul 2018 · 2 mos · Bangalore

We used the concepts of Machine Learning, NLP, and Speech Recognition to develop a Custom Domain specialized speech to text for retail use cases such as call centers that go beyond retail-specific taxonomy and needs to factor in context when identifying alphanumeric codes that are transient.

Machine LearningNLPSpeech Recognition