Senior Data Architect/Engineer, Confluent
$183.1-215.2k
+ Annual bonus + Equity
Data streaming platform
Open for applications
Data streaming platform
1001+ employees
Open for applications
$183.1-215.2k
+ Annual bonus + Equity
1001+ employees
Company mission
Founded by the team that built Apache Kafka, their mission is to make managing Kafka easy.
Role
Who you are
- Bachelor's or Master's degree in Computer Science, Information Systems, or a related field
- 10+ years of experience in data engineering, with a focus on designing and implementing data warehouses, data modeling, ETL processes, and data transformation pipelines
- Experience with cloud-based data platforms (BigQuery) and components of the modern data stack
- Strong expertise in SQL, Python, and data engineering tools and frameworks
- Experience with CI/CD principles and tools (e.g., Git, Terraform, Docker)
- Knowledge of data governance principles, data quality management, and regulatory compliance
- Experience with Airflow orchestration for scheduling and managing workflows
- GCP experience, including familiarity with Google Cloud services such as BigQuery, & Dataflow
- Experience with Kafka, Data Build Tool (DBT)
- Excellent communication, leadership, and collaboration skills
- Ability to work in a fast-paced, dynamic environment and lead a team to deliver high-quality results
What the job involves
- We’re seeking an experienced and highly skilled Staff Data Architect/Engineer to help design our own central nervous system
- The Data Architect/Engineer is a senior technical contributor responsible for the design, technical requirements, and evolution of Confluent’s cloud data strategy
- The Data Architect/Engineer will be both responsible for overall functional & technical design but also governance, lineage, and data quality processes
- Own Confluent’s overall data warehouse architecture
- Design, architect, and maintain the data warehouse infrastructure to support current analytics, ML & AI needs and address future challenges
- Create and maintain data models, architecture patterns, and schemas that consider security, performance, scalability, and business needs
- Implement tools to support data modeling, orchestration and data pipelines such as DBT
- Develop and manage data pipelines, ensuring data quality, reliability, and scalability
- Collaborate with cross-functional teams to understand data requirements and deliver solutions that meet business needs
- Establish and enforce data governance policies, standards, procedures, and best practices to manage data integrity, quality, and lifecycle
- Ensure alignment between Confluent’s batch and real-time architecture teams
- Maintain detailed documentation of data architecture and systems to ensure all team members can understand and implement the systems effectively
- Stay updated with industry trends, technologies, and best practices in data engineering and analytics
Otta's take
Xav Kearney
CTO of Otta
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.
Insights
Some candidates hear
back within 2 weeks
27% female employees
14% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Apr 2020
$250m
SERIES E
Jan 2019
$125m
SERIES D
Total funding: $455.9m
Company values
- Earn Our Customers' Love - Our customers are the lifeblood of our business and our most important stakeholder. We strive to earn their love with everything we do
- To Build a Great Company, Build a Great Team - We believe that an important part of building a great company is making sure that our employees are the best they can be.
- Smart, Humble, and Empathetic - Our employees appreciate, benefit, and learn from working with other smart, humble, and empathetic people. We strive to hire those who care deeply about others and interact with empathy towards our customers, partners, and employees.
- Be Fired up and Get It Done - As much as we benefit from working with smart, humble, and empathetic employees, we also need to “get it done” to pursue our enormous market opportunity. We are in hyper-growth mode and are scaling to fill the demands of the market and our current and future customers.
- Tasteful not Wasteful - We want to invest in areas that matter the most -- in other words, spend “tastefully,” not wastefully. We believe that thoughtful spending is essential to building a high-quality business.
- One Team - It is critical that we act as and make decisions as a unified company, doing our best to optimize globally rather than locally. This means doing our best to avoid the misalignments that some companies can be prone to. It means recognizing that when employees and teams succeed, Confluent as a whole succeeds.
Company HQ
Mountain View, California
Articles
Founders
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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