Akhil Kondapaneni

Associate Consultant

Toronto, Ontario, Canada0 mo experience

Key Highlights

Expert in Kafka and Apache Flink for real-time data processing.
Proven track record in cloud migration and hybrid solutions.
Strong background in secure data management and encryption.

Stackforce AI infers this person is a Cloud Computing and Fintech specialist with expertise in data streaming and security.

Contact

Skills

Core Skills

Apache FlinkConfluent KafkaKafkaNode.js

Other Skills

Google Cloud Platform (GCP)Spring BootKubernetesSpring FrameworkJavaAzureApache KafkaKafka connectKafka StreamsKSQLDockerTerraformJenkinsGrafanaPrometheus

About

Seasoned engineer with a strong focus on diverse cloud platforms. Proficient in Kafka & Apache Flink, I specialize in leveraging innovative technologies to build robust solutions. A proactive learner, I excel in problem-solving and thrive on exploring the latest advancements in Data streaming, Cloud, and DevOps .

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Psyncopate technologies, inc.

Senior Solutions Consultant

Mar 2024 – Present · 2 yrs 2 mos · Toronto, Ontario, Canada · Remote

Developed a hybrid connect solution using Confluent for Kubernetes (CFK) to integrate on-premises Confluent Kafka Connect with Confluent Cloud.
Leveraged Confluent's Secret Provider for externalizing secrets, ensuring secure management of sensitive data across hybrid Kafka Connect deployments.
Utilized Single Message Transforms (SMT) to clean Change Data Capture (CDC) records from Debezium connectors.
Integrated RBAC into Confluent Control Center to enable authentication and secure access for the hybrid connect project.
Implemented Cluster Linking via CFK to mirror on-premises topics on Confluent Cloud, enabling efficient data replication and failover.
Successfully migrated from on-premises Confluent Platform to Confluent Cloud, ensuring seamless integration and enhanced cloud capabilities.
Created and conducted detailed workshops on Apache Flink, covering foundational concepts as well as advanced topics like stateful stream processing, windowing, and event time processing. These workshops were designed to empower teams with the skills needed to leverage Flink for real-time data processing.
Extensive Flink SQL Query Development: Wrote complex Flink SQL queries to handle various use cases, including real-time analytics, data enrichment
Designed and implemented stream processing pipelines that integrated Apache Flink with Kafka. This included setting up Flink jobs that consumed Kafka topics, applied real-time transformations, and produced results back to Kafka or other sinks.
Developed custom Flink jobs tailored to meet specific business needs, such as real-time fraud detection, monitoring, and predictive analytics. These jobs utilized advanced Flink features like keyed state, timers, and custom operators.
Managed and deployed Flink clusters on Kubernetes, ensuring high availability, scalability, and efficient resource management.

Google Cloud Platform (GCP)Spring BootConfluent KafkaApache FlinkKafkaKubernetes

Scotiabank

Platform Engineer

May 2020 – Mar 2024 · 3 yrs 10 mos · Toronto, Ontario, Canada

Spearheaded the development and deployment of the first automated self-serve Kafka connect project on the Azure cloud platform, helped our tenants move data from Azure EventHub onto Kafka topics. This played a pivotal role in the launch of Scene+ platform.
Developed automated scripts to securely pull sensitive data from Azure Key Vault, required for spinning up Kafka Connect and connectors. This implementation improved the overall security posture and streamlined the provisioning process. This also ensured that we leverage a centralized Vault for all secret management tasks
Played a major role in the development of a Node.js encryption library used in all Kafkajs applications.
Successfully integrated data encryption at rest using libraries from Confluent and in-house teams, ensuring data at rest is encrypted within the topics.
Built robust producer and consumer applications in both Java and Node.js leveraging Confluent Kafka
Leveraged Kafka Connect and Connect SMTs (Single Message Transforms) for data transformation and filtering wherever required, enabling seamless data processing and enhancing data quality in real-time
Worked extensively on the Schema Registry side of things, especially for Java and Node.js applications. Implemented schema evolution strategies and versioning techniques, ensuring seamless compatibility and data integrity across different application versions.
Proved instrumental in resolving critical issues in production and elsewhere, leveraging expertise in Kafka and other tools.

Google Cloud Platform (GCP)Spring FrameworkNode.jsKafkaJava