Data Engineer (Kafka and Streaming)

Maxwell Bond; Liverpool; Hybrid; GBP 55,000 - 75,000; Full time

Job summary

A leading financial services organization seeks a Data Engineer focusing on streaming technologies like Apache Kafka and Confluent Cloud. This role offers the chance to influence data strategy, work with innovative technologies, and be an integral part of a dynamic data engineering team. With a collaborative approach, you will design data pipelines and frameworks while ensuring high data quality and governance.

Benefits

Ownership of key architecture decisions

Opportunity to influence data strategy

Freedom to explore new technologies

Qualifications

• 5+ years of experience as Data Engineer or related.
• Hands-on with Apache Kafka and Confluent Cloud vital.
• Self-starter with collaborative mindset.

Responsibilities

• Design and maintain real-time data streaming pipelines using Kafka.
• Architect scalable data ingestion frameworks.
• Collaborate with stakeholders for high-quality datasets.

Skills

Streaming Technologies

Apache Kafka

Data Engineering

Analytical Thinking

Python

Data Governance

Tools

Apache Spark

Databricks

NoSQL Technologies

Job description

Data Engineer – Financial Services | Strong Kafka/Streaming Focus- Liverpool/Hybrid – Up to £75K (DOE)

Our client, an innovative and rapidly expanding Financial Services organization, is seeking a 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:

• 5 + 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.