Job Description

Finance & Operations



Remote, United Kingdom



R02972

Description

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:

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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:

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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 Developing strong subject matter expertise and managing the SLAs for those data pipelines Set up and improve BI tooling and platforms to help the team create dynamic tools and reporting Partnering 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

Here are some 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 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:

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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, Mathematics, Statistics, Engineering, or related technical discipline Expert knowledge of SQL and relational & cloud database systems and concepts Strong knowledge of data architectures, data modelling and data infrastructure ecosystem Experience with enterprise business systems such as Salesforce, Marketo, Zendesk, Clari, Anaplan, etc Experience with ETL pipeline tools like Airflow, and DBT, and with code version control systems like Git Demonstrated ability to see the big picture and translate business needs into technical requirements Strong stakeholder management skills and ability to effectively prioritize competing demands The ability to communicate cross-functionally, derive requirements and architect shared datasets; the ability to synthesize, simplify, and explain complex problems to different types of audiences, including executives Proven track record of mentoring junior engineers and helping them grow technically The ability to thrive in a dynamic environment. That means being flexible and willing to jump in and do whatever it takes to be successful

What Gives You an Edge:

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Experience with Apache Kafka Knowledge of batch and streaming data architectures Product mindset to understand business needs, and come up with scalable engineering solutions Previous experience scaling data teams and establishing data engineering best practices Experience balancing technical debt with new feature development Success in translating business objectives into actionable technical roadmaps

Ready to build what's next? Let's get in motion.

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Come As You Are

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Belonging isn't a perk here. It's the baseline. We work across time zones and backgrounds, knowing the best ideas come from different perspectives. And we make space for everyone to lead, grow, and challenge what's possible.


We're proud to be an equal opportunity workplace. Employment decisions are based on job-related criteria, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by law.