Data Engineer I SC Cleared

Tyne and Wear Source: WhatJobs

£390–£500/day

Data Engineer / SC Cleared

390 - 500 per day (Inside IR35/Umbrella)

Duration: 14 Months (60 Weeks)

Location: Hybrid from either Newcastle, London, Manchester or Glasgow (2-3 days per week)

Start: ASAP

We are looking for an experienced Data Engineer to join a high-profile programme, delivering scalable and robust data solutions within a modern cloud-based environment. This is an excellent opportunity to work with cutting-edge technologies including AWS, Kafka, Kubernetes, Java, and Big Data platforms , helping organisations unlock the value of their data.

The Role

As a Data Engineer, you'll be responsible for designing, developing, and maintaining data solutions that support data generation, collection, processing, and consumption across the organisation. You'll work closely with technical and business stakeholders to build high-performing data pipelines, ensure data quality, and deliver reliable ETL processes.
This role requires someone who can provide technical leadership, contribute to key architectural decisions, and collaborate effectively across multiple teams while mentoring junior engineers.

Key Responsibilities

Design, develop, and maintain scalable data engineering solutions.
Build and optimise data pipelines to support large-scale data processing.
Implement ETL processes to migrate, transform, and deploy data across multiple platforms.
Ensure the quality, accuracy, and reliability of data across the estate.
Collaborate with cross-functional teams to understand business requirements and deliver effective data solutions.
Monitor, troubleshoot, and improve pipeline performance and stability.
Contribute to technical design discussions and key project decisions.
Act as a subject matter expert within the data engineering capability.
Mentor and support junior team members, promoting best practices and knowledge sharing.
Stay current with emerging technologies and industry trends to drive continuous improvement.

Required Skills & Experience

Strong commercial experience in Data Engineering .
Expert-level proficiency in Java .
Advanced experience with Amazon Web Services (AWS) .
Advanced experience with Apache Kafka .
Advanced experience with Kubernetes .
Experience working with Big Data technologies and engineering practices.
Proven experience building and maintaining enterprise-scale data pipelines.
Strong understanding of data modelling, ETL frameworks, and data quality management.
Experience working within Agile delivery environments.
Excellent stakeholder management and communication skills.