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Apache Kafka developer
Rishabh is a software engineer having 7+ years of experience designing real-time processing data pipelines and applications for analyzing both real-time and historical data.
Mahesh is a software engineer having 3+ years of experience developing real-time software applications that provide asynchronous service communication and quick data access.
John is a software engineer having 10+ years of experience designing real world data pipelines that provides easy data integration, quick data access, and real-time data processing.
Hire Top Talented Apache Kafka developers with UltraGenius
Apache Kafka is a distributed data store used for designing live streaming data pipelines and applications that are adaptable to data streams. Kafka combines messaging system, storage, and real-world streaming which provides storage and analyzation of both historical and real-world data.
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Want to hire Apache Kafka developers on your own? Here are the skills you must look for while hiring a Apache Kafka developer
Hiring Apache Kafka developers might be an intricate task for you if you are a non-technical manager. Apache Kafka is a software bus framework implementation which combines real-time data processing and analyzing data, messaging, and storage of data. Kafka automatically manages the customers in the case of system failure and is able to handle multiple subscribers at once. But, hiring the most skilled Apache Kafka developers among thousands of developers is a challenging task for anyone. So, UltraGenius is here to assist you while recruiting the top talented Apache Kafka developers on your own. UltraGenius understands your job requirements and gets you only the top developers who havedetailed knowledge working with Kafka.
The following skills you must look for while hiring a Apache Kafka developer –
Steadfast knowledge of Java
Knowledge of Java is very good for a Apache Kafka developer. Apache Kafka is mostly written in Java and Scala and the developer can take advantage of various libraries provided by Java which have multiple additional features associated with it. Hands-on experience with Java will benefit a Apache Kafka developers before experimenting other platforms.
Knowledge of Scala programming language
Scala is built for designing, developing, and testing applications based on cloud. Scala has in-built classes which provides the necessary aspects of generating data into Kafka. Moreover, the static types in Scala helps to avoid defects/bugs in complex software applications.
Familiarity with Kafka Producer and Consumer APIs
Producer APIs produce messages to Kafka topics which are stored in different topic partitions. Kafka Producer publishes records to the Kafka cluster and makes sure that it is thread-safe. The consumers subscribe the Kafka topics. Apache Kafka keeps record of all the messages which are published regardless of their consumption for a configurable time period.
Knowledge of librdkafka library
librdkafka is a multi-threaded C/C++ client library which is designed to be used on modern hardware reducing memory usage by minimizing memory copying. The payload of produced / consumed messages can be passed without any need for copying (if desired by an application). librdkafka provides high throughput via message batching which is the process of waiting for certain number of messages to get collected in queues before sending them off in a large set to the peer.
Experienced in working with Version Control System (VCS)
Hire Kafka must know how to use Git, which is a version control system and mostly used by development teams. With it, they can collaborate efficiently on the code while being able to organize your work with ease. The Kafka developers should also know some other commands like add, push, pull and commit as well as branching and merging (which are essential tools for independent coding).
Excellent understanding of testing types and tools
There are several testing systems like Testcontainers, Confluent Cloud, and Docker which helps Kafka developers write good tests and design continuous integration pipelines. Kafka’s native libraries and streams such as TopologyTestDriver simplifies input/output testing. The Kafka developer must know about Unit testing, Integration testing, Performance testing, Chaos testing, and Soak testing.
Familiarity with Kafka Streams
Apache Kafka provides a client library called Kafka Streams which is used for designing applications and microservices. The input and output data in Kafka streams is stored in the Kafka clusters format. Kafka Streams simplifies the writing and deploying of Scala and Java applications with the advantage of its server-side cluster technology. Kafka Streams are viable equally for small and large use-cases. Check the developer’s knowledge of Kafka Streams and whether the Kafka developer has implemented them.
Knowledge of message delivery semantics
Kafka provides the straightforward semantics for the delivery of the message. While publishing a message, it provides the notion of “committed” message to the log. Once the message is committed, it will not get lost as long as any broker to which this message is written who replicates the partition is still “alive”. Kafka Programmers must be aware of the message delivery semantics that include –
- at most once – means that messages are never re-delivered even if they are lost.
- at least once – means messages are re-delivered if they are lost.
- exactly once – means each message is delivered only one-time.
Familiarity with Connect APIs
Kafka provides the Connector APIs for implementing connectors which helps Kafka developers push data from Kafka into another sink data system or pull from a data system into Kafka. Kafka developers use pre-built connectors to copy data between Kafka and other data systems without any need to write code. Replicator, JMS Source, JDBC Source and Sink, Amazon S3 sink, Elasticsearch Service Sink, and HDFS 2 Sink are popular connectors used by the Kafka developers.
Knowledge of REST APIs
The Confluent REST Proxy provides a RESTful APIs for Kafka clusters which makes producing and consuming of messages simpler. REST APIs helps perform administrative actions without requiring any usage of native protocols and clients, ingesting messages into a real-time data processing framework which don’t have any support for Kafka. Most of the metadata about the clusters can be read using GET requests for the corresponding URLs.
Familiarity with Confluent and Confluent Cloud CLI
Confluent provides CLI which manages and uses Kafka topics, clusters, connectors, schemas, ksqlDB, and event streaming for Confluent Cloud and other platforms. The Kafka developer also uses Confluent Cloud CLI for creating and managing Apache Kafka applications.
Expertised working with Cloud platforms
Kafka makes it easier to deploy cloud applications with its multi-cloud data pipelines, real-time data processing and integration. Kafka developers must have experience working with any of the cloud service providers like – Google Cloud, Microsoft Azure, and Amazon AWS. As backing stores, Kafka uses Azure Managed Disks.
Knowledge of Event Streaming Patterns
Event Streaming Patterns provide simple, reusable architectural patterns that are well applied over event streaming systems. Check the Kafka developers’ knowledge of including process events as streams, integrations with external systems, sourcing data, etc.
Hands on experience with ksqlDB database
Kafka is an event streaming platforms which provides a fault-tolerant storage system, processes streams of events in real-time processing environments. Kafka uses ksqlDB database, which is an event streaming database that enables Kafka developers design stream processing applications. ksqlDB stores metadata in the interactive mode. ksqlDB helps in continuous modifications, creates best materialized views, and serves as an excellent tool for designing microservices.
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Apache Kafka is an excellent messaging system widely known for designing real-time data streaming applications and pipelines, effectively retains records in the order of their generation, and publish and subscribe to records streams. Kafka automatically manages the customers in the case of system failure and is able to handle multiple subscribers at once. But recruiting the best Kafka developers is not an easy task when a large no. of Apache Kafka developers are competing to grab the job opportunities.
Frequently Asked Questions
UltraGenius is one of the leading platforms for hiring remote talent and connecting developers and part-time developers with Silicon Valley businesses. We focus on finding the best talents who will perform extremely well and will be easily integrated into your teams. We filter out only the top 1% most skilled freelance developers among the 50K+ developers who have applied on our platform. Candidates have to prove their self-reported experience by giving UltraGenius’ s skill tests.
UltraGenius first tests the developer’s skill set by conducting a two and half hour hiring test. Our hiring test judges a candidate on all aspects like aptitude, case study analysis, verbal and reasoning, coding questions based on data structures and algorithms, software engineering, system design, and more. Then, there is another round for the candidates who are selected from this round called “Higher-level Assessment Skill Test”, which is a video round that deeply analyzes Kafka developers’ major skills and asks questions about the projects they have worked upon.
Fill up the form which is on every hiring freelancers’ page and we will inform you once we select the top 1% Kafka developers matching your job requirements. After analyzing the candidates based on their resumes and two assessment tests, we provide you the feedback quickly. And if the developers selected by our team are fit for your job role, then we also provide the onboarding.
UltraGenius offers you only the most skilled developers who are top 1% among the 50K+ developers who have applied on our platform. After a rigorous selection and testing process, we sort out only the top candidates for you. You can check out UltraGenius’ s selection process for hiring Kafka developers.