Junior to Mid-Level Data Engineer – Financial Services | Strong Kafka/Streaming Focus- London/Hybrid (2 days per week) – Up to £70K (DOE)

Our client, an innovative and rapidly expanding Financial Services organization, is seeking a Junior to Mid-Level Data Engineer to join their highly technical data team. This is a unique opportunity to be part of a forward-thinking company where data is central to strategic decision-making.
We’re looking for someone who brings hands-on experience in streaming data architectures, particularly with Apache Kafka and Confluent Cloud, and is eager to shape the future of scalable, real-time data pipelines. You’ll work closely with both the core Data Engineering team and the Data Science function, bridging the gap between model development and production-grade data infrastructure.
What You’ll Do:
  • Design, build, and maintain real-time data streaming pipelines using Apache Kafka and Confluent Cloud.
  • Architect and implement robust, scalable data ingestion frameworks for batch and streaming use cases.
  • Collaborate with stakeholders to deliver high-quality, reliable datasets to live analytical platforms and machine learning environments.
  • Serve as a technical advisor on data infrastructure design across the business.
  • Proactively identify improvements and contribute to evolving best practices, with freedom to experiment and implement new technologies or architectures.
  • Act as a bridge between Data Engineering and Data Science, ensuring seamless integration between pipelines and model workflows.
  • Support data governance, quality, and observability efforts across the data estate.
What We’re Looking For:
  • 2+ years of experience in a Data Engineering or related role.
  • Strong experience with streaming technologies such as Kafka, Kafka Streams, and/or Confluent Cloud (must-have).
  • Solid knowledge of Apache Spark and Databricks.
  • Proficiency in Python for data processing and automation.
  • Familiarity with NoSQL technologies (e.g., MongoDB, Cassandra, or DynamoDB).
  • Exposure to machine learning pipelines or close collaboration with Data Science teams is a plus.
  • A self-starter with strong analytical thinking and a “leave it better than you found it” attitude.
  • Ability to operate independently and also collaborate effectively across teams.
  • Strong communication skills and experience engaging with technical and non-technical stakeholders.
Why Join?
  • Be part of a highly respected and technically advanced data team at the heart of a thriving business.
  • Get ownership of key architecture decisions and the freedom to try new ideas.
  • Play a pivotal role in scaling the company’s data capabilities during a phase of significant growth.
  • Influence data strategy across business units and leave a lasting impact.