Lead Data Engineer (MongoDB, Kafka, Java)

Salary:Competitive plus generous benefits package

Location:Hybrid working with occasional travel to key sites across the UK (London, Bristol, Gloucester, Edinburgh)

A leading financial services organization is undergoing a major digital transformation, placing technology at the heart of its growth strategy. They are investing in an enhanced in-house capability to reshape the future of banking. This transformation presents a unique opportunity for a forward-thinking IT professional to play a critical role in building next-generation data-driven systems.

The Lead Data Engineer will be a central figure in designing, developing, and deploying mission-critical data applications and systems. Combining deep technical expertise with leadership skills, the role involves driving innovation, managing complex projects, and mentoring junior engineers. The successful candidate will set the technical direction for projects, ensuring that solutions align with business goals while maintaining the highest quality standards.

Key Responsibilities

• Lead the design and implementation of data-driven solutions across the enterprise.
• Collaborate with cross-functional teams to align technology strategy with business objectives.
• Mentor and support junior engineers, fostering a culture of continuous learning.
• Ensure data systems are scalable, maintainable, and secure.
• Drive improvements in processes, technologies, and systems architecture.

What You’ll Bring

Essential Skills & Experience:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent experience.
• Expertise in agile application development using Java and microservices, with a focus on MongoDB and Kafka.
• Strong proficiency in data architecture, design patterns, and best practices.
• Experience with CI/CD pipelines and version control systems like Git.
• Proven ability to design scalable, real-time data applications.

Technical Expertise:

Must have modern, recent experience with MongoDB and Kafka in a data engineering capacity

Real-Time Data Applications

• Data Management: MongoDB, Cassandra/ScyllaDB
• Data Integration: Kafka, Kafka Streams, Java, APIs (GraphQL)

Data Analytics Applications:

• Data Management: Teradata, Azure Data Lake, Snowflake, Databricks
• Data Modelling: Dimensional Modelling, Kimball Design
• Data Integration: IBM DataStage, SQL, Azure Data Factory, AWS Glue
• Batch Orchestration: TWS/OPC, JCL
• Data Visualization: Power BI
• Data Analytics: SAS or comparable tools

What’s in It for You

• Hybrid & Flexible Working:Supporting a healthy work/life balance.
• Reward & Benefits Package:A personalized benefits program.
• Dynamic Work Environment:A collaborative and inclusive culture.
• Career Growth:Opportunities for development and progression.