Data Engineer

Stepney
3 days ago
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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

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