Senior Data Engineer - Product

The Engineering (Tech) Team is responsible for all Feedzai product development. Together with Product Management and Data Science, we build the next generation of tools to catch fraud in real-time with a machine learning first approach. Formed by engineers and managed by engineers, at Feedzai, you will find one of the most talented teams out there, from junior to senior engineers.

We are fast-paced and provide a safe, open, and collaborative environment that encourages us to lean in, try new things and discover our potential with continuous learning for everyone.

While building the best value for our customers, you will work with a wide range of technical challenges. Such as building distributed systems that need to operate 24/7 and ultra-low latencies, solving UI/UX problems to help fraud analysts to fight fraud more efficiently. In addition, designing extensive databases from relational, NoSQL and graphs, validate and develop new data science techniques and algorithms.

The Data Platform team is responsible for building and operating the core data infrastructure that powers Feedzai's AI-driven products. We own the full lifecycle of the platform, including our query engines, data ingestion, schema management, and pipeline orchestration. We operate under a 'you-build-it-you-run-it' model, managing highly available, multi-tenant cloud services on Kubernetes. Formed by engineers and managed by engineers, we partner with Product Engineering, Data Science, and Research teams to ensure Feedzai's data ecosystem is scalable, reliable, and secure, while providing the tooling needed for our internal customers to innovate and deliver at scale.

You:

We are looking for a Senior Data Engineer with a knack for building large-scale, cloud-native data processing systems to help us design, implement, and operate Feedzai's Data Platform.

You'll play a critical role in developing the core infrastructure used across the entire organization to power our AI-driven financial crime-fighting products. The Data Platform team is responsible for ingesting, processing, and serving mission-critical data while meeting stringent performance, security, and reliability targets.

• You are a data engineer at heart, skilled in building scalable data platforms and distributed systems. You enjoy solving complex data challenges, optimizing performance, and ensuring the reliability of mission-critical pipelines.
• You are curious about new data technologies but focus on delivering production-quality software that enables other teams to build innovative products.
• You combine speed with rigor: moving fast while maintaining high standards for code quality, security, and production readiness.
• You think in platforms, not just features, and enjoy building reusable frameworks that empower teams and set technical direction.

Your Day-to-Day

• Design and build large-scale distributed data processing systems from the ground up.
• Build and operate self-service data platform features and tooling for product engineers across Feedzai.
• Review, optimize, and approve pipeline and infrastructure code written by other teams to ensure performance, reliability, and architectural consistency.
• Maintain, monitor, and scale a select set of mission-critical, platform-level data pipelines, including horizontal scaling of high-throughput components under increasing load.
• Operate the systems you build as always-on, highly available cloud services on Kubernetes, with an ownership mindset from design through incident response.
• Collaborate with backend engineers, product managers, data scientists, and researchers to execute Feedzai's product roadmap and platform hardening initiatives.
• You actively apply AI tools to streamline projects and workflows, suggesting AI integration for existing processes.
• Mentor engineers and raise the technical bar through design and code reviews across the team.
• Lead small groups to deliver complex features end-to-end, ensuring quality and technical alignment.

You Have & You Know-How

• 5+ years of experience building and operating distributed data-driven systems.
• Degree in Computer Science (BSc/MSc) or equivalent technical background.
• Strong coding fundamentals in Java and/or Python, with experience developing distributed backend applications from scratch (e.g. Quarkus services, Spark jobs).
• Hands-on infrastructure skills: comfortable operating Linux-based cloud infrastructure and designing clean APIs.
• Big data & pipeline expertise: hands-on experience developing, debugging, and tuning distributed batch processing, messaging systems, and data storage architectures.
• Production DevOps mindset: comfortable in continuous delivery environments where teams build, deploy, monitor, and maintain their own services (you-build-it-you-run-it).
• Autonomous problem solver: able to bring new ideas to the team and tackle complex architectural challenges independently.
• Strong communication skills, with an ability to clearly articulate tradeoffs and decisions to both technical and non-technical stakeholders.

Preferred/Valued Qualifications and Skills: 

• Prior experience working on dedicated Data Platform or Data Infrastructure initiatives.
• Hands-on experience with our stack: Kubernetes, Apache Spark, Trino, Apache Iceberg, Nessie, Apache Airflow, Kafka, AWS (S3/Glue), Snowflake, and Quarkus.
• Experience building multi-tenant cloud services.
• Familiarity with JupyterHub / JupyterLab enterprise workflows.
• Contributions to open-source software (OSS) projects.

The Product Team builds our product to disrupt the financial crime industry from a data-led approach. We partner with our clients using a holistic lens and have result-driven solutions to manage financial risk with a cloud-first platform and a world-class UX interface. Being part of this team, you have a voice in planning, strategizing, and challenging the status quo. Your thoughts and ideas are valued. Our fast-paced and open environment encourages us to lean in, try new things, and  discover our potential. We define and act on what could be in tomorrow's world, not on what is today. Join Us!

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