Lokesh Shekar

VP of Engineering

San Francisco, California, United States16 yrs 1 mo experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in cloud-native data governance solutions.
Proven leadership in engineering team management.
Extensive experience in SaaS and cloud infrastructure.

Stackforce AI infers this person is a SaaS-focused engineering leader with expertise in cloud infrastructure and data governance.

Contact

Skills

Core Skills

Data GovernanceCloud InfrastructureEnterprise SoftwareInfrastructure

Other Skills

Amazon Web Services (AWS)Microsoft AzureLeadershipSoftware as a Service (SaaS)Google Cloud Platform (GCP)KubernetesDockerSoftware DevelopmentDebuggingDistributed SystemsGdbJavaGoPythonC

About

Experience

16 yrs 1 mo

Total Experience

2 yrs 8 mos

Average Tenure

9 yrs

Current Experience

Confluent

2 roles

Senior Engineering Manager

Promoted

Dec 2020 – Present · 5 yrs 5 mos

Leading an Engineering team responsible for providing Stream Governance Platform (https://www.confluent.io/product/stream-governance/). Its a cloud-native, fully managed data governance suite for Apache Kafka and real time data. Currently available on AWS, GCP and Azure.
We help customers deliver trusted, high quality data streams and maintain real-time data integrity with explicitly defined data contracts and schema management for your streaming data using
Schema Registry: Define and enforce universal data standards that enable scalable data compatibility.
Schema Validation: Verify, on the broker side, that messages use valid schemas when assigned to a specific destination topic.
Schema Linking: Share schemas across cloud and hybrid environments that sync in real time.
Data Quality Rules: Create customizable rules to enforce data semantics and avoid data quality issues
Previously led a team building Confluent for Kubernetes, a product that simplifies running Confluent Platform (Kafka, KSQL, Connect, to name a few) as a cloud-native system on Kubernetes, whether on-premises or in the cloud. Confluent for Kubernetes automates deployment, management, and scaling of Confluent Platform clusters at scale, managing their complete lifecycle. It is used at a massive scale as part of our managed service, Confluent Cloud.
To know more about how Confluent for Kubernetes provides Life cycle Management of complex stateful applications such as Kafka, providing seamless rolling upgrade, elasticity, and scaling aspects, please visit https://www.confluent.io/confluent-operator/
Our vision is to build a robust, distributed cloud-agnostic control plane with Confluent Platform's self-healing and auto-scaling capabilities.

Data GovernanceAmazon Web Services (AWS)InfrastructureMicrosoft AzureLeadershipSoftware as a Service (SaaS)+3

Staff Software Engineer

May 2017 – Dec 2020 · 3 yrs 7 mos

One of the founding engineers for building Control Plane for Confluent Cloud (Hosted and Managed SAAS offering of Confluent Platform)
https://www.confluent.io/confluent-cloud/

KubernetesAmazon Web Services (AWS)InfrastructureMicrosoft AzureGoogle Cloud Platform (GCP)Cloud Infrastructure+1

Infoblox

2 roles

Staff Software Engineer

Feb 2017 – Apr 2017 · 2 mos · Santa Clara

- Developed a platform for application message delivery from Cloud to Onprem devices.

KubernetesAmazon Web Services (AWS)InfrastructureGoogle Cloud Platform (GCP)Cloud Infrastructure

Senior Software Engineer, Cloud

May 2015 – Jan 2017 · 1 yr 8 mos · Santa Clara

Working on 'Infoblox DNS Firewall as a Service' which is a AWS cloud-based recursive DNS infrastructure. It is based on microservices architecture using Docker containers and developed in an agile methodology.
Developed Policy Manager for fetching the user policies and threat feed, creating and distributing relevant configuration to containers.
Designed and implemented monitoring, metric collection and auto scaling of Docker containers.
Implemented synchronization of AWS Route53 DNS zones and record sets into Infoblox Grid using AWS Route53 APIs for Hybrid Cloud deployments.
Programming Language: Golang and Python
Cloud: AWS and Azure.
Technologies: Docker, SaaS architecture.

InfrastructureGoogle Cloud Platform (GCP)Cloud Infrastructure

Juniper networks

Software Engineer 3

Jul 2012 – May 2015 · 2 yrs 10 mos · Sunnyvale

Involved in the design, development and support for layer 2 and layer 3 Multicast solution in Control Plane on QFabric (Fabric based Data Center Switch) product.
Implemented ‘fabric-optimized-distribution’ feature to increase the maximum supported L3 multicast flows.
Developed ‘make-before-break’ multicast feature of creating new multicast fabric paths before tearing down old paths.
Worked on several other features and enhancements to provide a highly scalable, highly available distributed system with faster convergence.

Infrastructure

Ericsson

Research Intern

Jan 2012 – May 2012 · 4 mos · San Jose, California

Built a basic prototype for network virtualization using Software Defined Networking concepts for R&D team.
Worked on REST APIs, REST server/client using staff framework, Onix controller (Openflow) and mininet.

Cisco systems

Software Intern

May 2011 – Aug 2011 · 3 mos · San Jose, CA

Implemented passive measurement of ‘one-way delay’ performance metric in the media monitoring component of Cisco IOS using C on UNIX platform.
Data plane changes include packet selection, data extraction and time stamping. Control plane changes include NTP synchronization, NetFlow export, data storage and correlation to calculate the metric.

Bosch engineering and business solutions

Software Engineer

Jul 2008 – Jul 2010 · 2 yrs · Bengaluru Area, India

Implemented Network Communication Software Component to handle raw value acquisition of numerous CAN messages and their subsequent physical value conversion.
Creating Interfaces, error diagnosis, bus off, power on and plausibility monitoring.
Responsibilities included software requirement analysis, high level and low level designing, coding using C and C++ programming languages, debugging and unit testing of the components.