Data Engineer - Streaming

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

My client, an innovative and rapidly expanding Financial Services organisation, 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.

I'm 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 I'm 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.