Data Engineer (SC Clearance Required) in Chelmsford

Data Engineer (SC Clearance Required) in Chelmsford

Chelmsford Full-Time 50000 - 70000 £ / 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 career advancement potential.
  • 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 is essential.

The predicted salary is between 50000 - 70000 £ 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 Chelmsford 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 Chelmsford

Tip Number 1

Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.

Tip Number 2

Prepare for interviews by practising common questions and showcasing your skills. We recommend doing mock interviews with friends or using online platforms to get comfortable.

Tip Number 3

Show off your projects! If you’ve worked on any relevant data engineering projects, make sure to highlight them during interviews. Real-world examples can set you apart from the crowd.

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 at Amber Labs. Plus, we love seeing candidates who are proactive!

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

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 ETL Inside Out

Make sure you can talk confidently about your experience with ETL processes. Be ready to discuss specific projects where you've extracted, transformed, and loaded data, and how you designed reusable transformation pipelines. This will show that you understand the core technical skills required for the role.

Showcase Your Cloud Expertise

Since AWS experience is essential, brush up on your knowledge of services like S3, Lambda, and Glue. Prepare examples of how you've designed and supported cloud-native data platforms, and be ready to explain how you ensure data security and reliability in AWS environments.

Demonstrate Collaboration Skills

This role requires strong collaboration with various stakeholders. Think of instances where you've worked closely with data analysts or business stakeholders. Be prepared to share how you translated their requirements into technical solutions and communicated complex concepts clearly.

Prepare for Technical Questions

Expect technical questions related to streaming technologies and messaging systems like Apache Kafka. Brush up on your understanding of event-driven data pipelines and be ready to discuss how you handle large datasets. Practising these topics will help you feel more confident during the interview.