Data Engineer (SC Clearance Required) in Preston

Data Engineer (SC Clearance Required) in Preston

Preston Full-Time 50000 - 65000 £ / year (est.) Working from home possible
Amber Labs

At a Glance

  • Tasks: Join a dynamic team to build and optimise data pipelines for impactful projects.
  • Company: Amber Labs, a forward-thinking digital consultancy transforming the UK public sector.
  • Benefits: Fully remote work, competitive salary, and opportunities for professional growth.
  • Other info: Collaborative environment with strong focus on innovation and career development.
  • Why this job: Make a real difference in digital transformation while working with cutting-edge technologies.
  • Qualifications: Experience in data engineering, ETL processes, and cloud infrastructure required.

The predicted salary is between 50000 - 65000 £ per year.

Location: Fully remote (no multi-site travel required)

Contract Type: Permanent / or 12-month Fixed Term Contract (with a view going perm)

Employer: Amber Labs – Digital Consultancy

Clearance: Active SC Clearance required.

Start Date: Immediate

About Amber Labs

Amber Labs is a forward-thinking digital consultancy delivering innovative cloud, data, and DevOps solutions across the UK public sector. We specialise in helping organisations achieve digital transformation at pace while maintaining the highest security and governance standards.

We are seeking a Data Engineer who can integrate into an existing data delivery team, operate with strong autonomy, and contribute meaningfully from day one. The successful candidate must demonstrate strategic technical ownership, the ability to lead data engineering streams, and — critically — prior exposure to the end client or wider public sector.

Role Overview

This role is suited to a strong mid-to-senior level engineer with solid experience in data engineering, ETL processes, cloud infrastructure, and streaming technologies. The successful candidate will work closely with analysts, data consumers, and technical stakeholders to ensure data is reliable, accessible, and fit for operational and analytical use. The role combines hands-on engineering with strong collaboration and stakeholder engagement.

ETL & Data Engineering Practices (Essential)

  • Strong understanding of ETL and modern data engineering practices.
  • Proven experience:
    • Extracting and transforming raw data.
    • Designing reusable transformation pipelines.
    • Delivering structured datasets for reporting and analytics.
  • Ability to:
    • Build maintainable and scalable pipelines
    • Optimise data flows and processing efficiency
    • Handle large and complex datasets reliably

Core Technical Skills

Streaming & Messaging Technologies

  • Good practical understanding of Apache Kafka
  • Experience working with:
    • Event-driven data pipelines
    • Streaming ingestion patterns
    • Asynchronous processing architectures
  • Understanding of:
    • Topics and partitions
    • Consumer groups
    • Data reliability and ordering considerations

AWS & Cloud Data Engineering (Essential)

  • Strong hands-on experience with Amazon Web Services
  • Experience designing and supporting cloud-native data platforms
  • Strong understanding of:
    • Data storage patterns
    • Scalability and reliability
    • Secure data handling in AWS environments
  • Experience with AWS services such as: S3/ Lambda / IAM / Glue Redshift or equivalent data services

Infrastructure as Code

  • Hands-on experience with Terraform
  • Ability to:
    • Provision and manage cloud infrastructure
    • Maintain reusable and version-controlled infrastructure definitions

Databricks (Nice to Have)

  • Exposure to or experience with Databricks
  • Understanding of:
    • Distributed data processing
    • Notebook-driven development
    • Spark-based workloads

Collaboration & Stakeholder Engagement

  • Work closely with:
    • Data analysts / Data scientists / Engineers / Business stakeholders
  • Translate business and analytical requirements into technical solutions
  • Communicate technical concepts clearly to non-technical audiences where needed

Apply Now and help shape the future of UK digital services with Amber Labs.

Data Engineer (SC Clearance Required) in Preston employer: Amber Labs

Amber Labs is an exceptional employer, offering a fully remote work environment that promotes flexibility and work-life balance. With a strong focus on employee growth, we provide opportunities for professional development in cutting-edge technologies while fostering a collaborative culture that values innovation and strategic thinking. Join us to be part of a forward-thinking digital consultancy that is making a meaningful impact in the UK public sector.

Amber Labs

Contact Details:

Amber Labs Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Engineer (SC Clearance Required) in Preston

Tip Number 1

Network like a pro! Reach out to your connections in the industry, especially those who work at Amber Labs or similar companies. A friendly chat can sometimes lead to job opportunities that aren't even advertised yet.

Tip Number 2

Prepare for interviews by brushing up on your technical skills and understanding of data engineering practices. Be ready to discuss your experience with ETL processes and cloud infrastructure, as these are key for the role.

Tip Number 3

Showcase your projects! Whether it's through a portfolio or GitHub, having tangible examples of your work can really set you apart. Highlight any experience with AWS and streaming technologies, as these are crucial for the position.

Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining Amber Labs and contributing to their mission.

We think you need these skills to ace Data Engineer (SC Clearance Required) in Preston

ETL Processes
Data Engineering Practices
Apache Kafka
Event-driven Data Pipelines
Asynchronous Processing Architectures
Amazon Web Services (AWS)
Cloud-native Data Platforms

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with ETL processes, cloud infrastructure, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our team. Be sure to mention your experience with AWS and streaming technologies, as these are key for us.

Showcase Your Technical Skills:When filling out your application, don't hold back on showcasing your technical skills. Mention specific tools and technologies you've used, like Apache Kafka or Terraform. We love seeing candidates who are hands-on and ready to dive into the tech!

Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it shows you're keen on joining our team at Amber Labs!

How to prepare for a job interview at Amber Labs

Know Your Tech Inside Out

Make sure you brush up on your knowledge of ETL processes, cloud infrastructure, and streaming technologies. Be ready to discuss your hands-on experience with AWS services like S3 and Lambda, as well as your understanding of Apache Kafka. The more specific examples you can provide, the better!

Showcase Your Problem-Solving Skills

Prepare to talk about how you've tackled complex data challenges in the past. Think of situations where you optimised data flows or built scalable pipelines. This will demonstrate your strategic technical ownership and ability to contribute from day one.

Engage with Stakeholders

Since this role involves collaboration with analysts and business stakeholders, be ready to discuss how you've translated business requirements into technical solutions. Highlight any experiences where you communicated complex concepts to non-technical audiences—this shows your versatility!

Be Ready for Scenario Questions

Expect scenario-based questions that test your practical understanding of data engineering practices. Prepare to explain how you would handle large datasets or design reusable transformation pipelines. Practising these scenarios can help you articulate your thought process clearly during the interview.