Associate Data Engineer, Confluent
Data streaming platform
Be an early applicant
Data streaming platform
1001+ employees
Be an early applicant
1001+ employees
Company mission
Founded by the team that built Apache Kafka, their mission is to make managing Kafka easy.
Role
Who you are
- This role is perfect for someone passionate about distributed systems, stream processing, and data engineering best practices
- A degree in Computer Science, Data Engineering, Software Engineering, or a related field
- Strong programming skills in Python, Java, or Scala
- Familiarity with SQL and NoSQL databases
- Basic understanding of Kafka, Flink, Spark, or other stream processing technologies (hands-on experience is a plus)
- Exposure to cloud computing platforms (AWS, GCP, or Azure) and infrastructure as code
- Interest in distributed systems, data architectures, and real-time analytics
- Strong problem-solving skills and a willingness to learn in a fast-paced environment
Desirable
- Experience with Apache Kafka
- Knowledge of batch and streaming data architectures
- Product mindset to understand business needs, and come up with scalable engineering solutions
What the job involves
- We are seeking a Data Engineer to join our team and contribute to building, optimising, and maintaining our real-time data streaming infrastructure
- You will work alongside experienced engineers to design, develop, and deploy scalable data pipelines that power mission-critical applications
- Design, develop, and maintain real-time data pipelines using Apache Kafka, Flink, and other streaming technologies
- Work with structured and unstructured data to enable analytics, monitoring, and event-driven applications
- Optimise data ingestion, transformation, and storage for performance, reliability, and scalability
- Collaborate with software engineers, data scientists, and DevOps teams to integrate data solutions into production environments
- Implement data quality, observability, and governance best practices
- Troubleshoot and resolve performance issues in streaming applications and distributed systems
Our take
Confluent is a commercial company built on top of the open-source Apache Kafka project. Confluent and Kafka have developed a streaming data technology that processes massive amounts of information in real-time.
The streaming database technology was developed at LinkedIn as a way of moving massive amounts of messages. The company decided to open-source that tech in 2011, and Confluent launched as the commercial arm in 2014.
While the base open-source component remains available for free download, it doesn’t include the additional tooling the company has built to make it easier for enterprises to use Kafka. Confluent's value add is in those additional tools, including a cloud version of the product and a marketplace for sharing extensions to the platform.
Confluent expanded strategic partnerships with Microsoft and acquired Immerok, and in 2023 expanded its cloud platform. 2024 saw further product expansions with the launch of the Confluent Migration Accelerator, all exemplifying how the company is living up to its name by rocket-boosting the benefits of Apache Kafka integration for companies.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 5 rounds)
Apr 2020
$250m
SERIES E
Jan 2019
$125m
SERIES D
Total funding: $455.9m
Company HQ
Mountain View, California
Leadership
Jay Kreps
(Co-Founder & CEO)Previously a Principal Engineer at LinkedIn.
Neha Narkhede
(Co-Founder & Board Member)Previously a Lead Engineer at LinkedIn and Oracle. They are an Investor/advisor for Gem, Block Party, Material Security, Abacus AI, Cortex Data, Yugabyte, Metaphor Data, Natalist, Common Room, and more.
Jun Rao
(Co-Founder)Previously a Senior Engineer at LinkedIn. Has a PhD in Computer Science from Columbia University.
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