Job Description

Employment Type: Full-Time Location Type: Remote

Company Overview

We’re not just building better tech. We’re rewriting how data moves and what the world can do with it. With Confluent, data doesn’t sit still. Our platform puts information in motion, streaming in near real-time so companies can react faster, build smarter, and deliver experiences as dynamic as the world around them.

It takes a certain kind of person to join this team. Those who ask hard questions, give honest feedback, and show up for each other. No egos, no solo acts. Just smart, curious humans pushing toward something bigger, together.

One Confluent. One Team. One Data Streaming Platform.

About the Role

The mission of the Data Science/Data Engineering team at Confluent is to serve as the central nervous system of all things data for the company: we build data and analytics infrastructure, insights, models and tools, to empower data-driven thinking, and optimize every part of the business. This position offers limitless opportunities for an ambitious data engineering leader to make an immediate and meaningful impact within a hyper-growth start-up, and contribute to a highly engaged open source community.

This is a partnership-heavy role. As a Team Lead within the Data organization, you will enable various functions of the company, i.e. Product, Engineering, Field Operations, Go-to-Market, etc., to be data-driven while providing leadership and direction to your team. As a Data Engineer, you will take on big data challenges in an agile way. You will participate and guide your team in building data pipelines that enable data scientists, analytics partners, operation teams, and executives to make data accessible to the entire company. You will also build data models to deliver insightful analytics while ensuring the highest standard in data integrity. You are encouraged to think out of the box and play with the latest technologies while exploring their limits. Successful candidates will have strong technical capabilities, leadership experience, a can-do attitude, and are highly collaborative.

What You Will Do

• Lead a team of data engineers, providing technical guidance, mentorship, and career development.
• Partner with stakeholders across the organization to understand business needs, prioritize features, and develop strategic data solutions.
• Break down complex projects into manageable tasks and assign them to team members based on their strengths and development goals.
• Design, build and launch extremely efficient and reliable data pipelines to move data across many platforms including Data Warehouse and real-time systems.
• Develop strong subject matter expertise and manage the SLAs for those data pipelines.
• Set up and improve BI tooling and platforms to help the team create dynamic tools and reporting.
• Partner with Data Scientists and business partners to develop internal data products to improve operational efficiencies organizationally.
• Foster a culture of innovation, collaboration, and technical excellence within your team.
• Represent the data engineering team in cross-functional meetings and advocate for technical best practices.

Examples of Our Work:

• Data Pipelines: Create new pipelines or rewrite existing pipelines using SQL, Python on Airflow & DBT.
• Data Quality and Anomaly Detection: Improve existing tools to detect anomalies in real-time and through offline metrics.
• Data Modeling: Partner with analytic consumers to improve existing datasets and build new ones.
• Technical Leadership: Guide the team towards maintaining a high technical bar while collaborating with stakeholders to deliver overall impact.

What You Will Bring

• 6+ years of experience in a Data Engineering role, with a focus on data warehouse technologies, data pipelines, and BI tooling.
• 1-3 years of team leadership, management, or equivalent project leadership experience (formal management preferred, but will consider dotted line management or technical leadership roles).
• Bachelor or advanced degree in Computer Science or a related field.