At a Glance
- Tasks: Lead the design and architecture of a next-gen data platform in FinTech.
- Company: Rapidly growing FinTech Infrastructure company based in London.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Join a dynamic team and mentor fellow engineers in a fast-paced environment.
- Why this job: Shape the future of financial technology with cutting-edge data solutions.
- Qualifications: 8+ years in Data Engineering with expertise in Kafka, Spark, and Flink.
Our client, a rapidly growing FinTech Infrastructure company based in London, is looking for a Staff Data Platform Engineer to define the architecture of its next-generation data platform. This is a senior individual contributor role where you'll lead the technical direction of the company's streaming and analytics platform while remaining hands-on with design, engineering, and implementation.
What You'll Be Working On
- Defining the technical vision and architecture for the company's enterprise data platform
- Designing large-scale streaming and batch processing systems handling billions of financial events
- Building high-performance data pipelines using Kafka, Spark, and Flink
- Developing Python services and automation supporting data ingestion, transformation, and orchestration
- Optimising Snowflake for high-performance analytics, reporting, and machine learning workloads
- Working closely with AI and Product teams to deliver trusted, real-time data for intelligent financial products
- Improving platform scalability, resilience, observability, and operational efficiency
- Establishing engineering standards, architectural best practices, and long-term technical direction for the data platform
- Mentoring senior engineers and leading technical design discussions across multiple engineering teams
- Helping shape the future of one of Europe's fastest-growing financial technology platforms
Experience Required
- 8+ years of experience in Data Engineering, Data Platform Engineering, Big Data Infrastructure, or Distributed Systems Engineering
- Extensive commercial experience with Apache Kafka in production environments
- Strong experience building distributed data processing systems using Apache Spark and Apache Flink
- Experience designing modern cloud-native data platforms using Snowflake or comparable cloud data warehouses
- Strong understanding of distributed systems, streaming architectures, and event-driven platforms
- Experience leading technical architecture and influencing engineering strategy without direct people management
- Passion for solving complex scalability and performance challenges through elegant engineering solutions
Nice to Have
- Experience building real-time fraud detection, payment processing, or financial analytics platforms
- Knowledge of Data Mesh, Lakehouse architectures, or Apache Iceberg
- Experience with Infrastructure as Code using Terraform
- OpenTelemetry, Prometheus, Grafana, or modern observability platforms
- Experience supporting AI or machine learning workloads on large-scale data platforms
- Previous Staff, Principal, or Lead Engineer experience within FinTech, Enterprise SaaS, or cloud-native technology companies
Staff Data Platform Engineer employer: XpertDirect
As a Data Engineering Lead, you'll be at the forefront of modernising our enterprise data platform, playing a pivotal role in our digital transformation journey. We pride ourselves on fostering a collaborative work culture that encourages innovation and mentorship, providing you with ample opportunities for professional growth within a dynamic international organisation. Join us to make a meaningful impact while enjoying excellent career progression and a supportive environment.
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We think this is how you could land Staff Data Platform Engineer
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We think you need these skills to ace Staff Data Platform Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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