At a Glance
- Tasks: Design and optimise data solutions in a cloud environment, focusing on ETL/ELT pipelines.
- Company: Join 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 team environment with a focus on innovation and security.
- Why this job: Make a real impact on digital transformation while working with cutting-edge technologies.
- Qualifications: Experience in Informatica, AWS, and Azure data platforms required.
The predicted salary is between 60000 - 75000 £ 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 Senior Data Engineer to design, build, and optimise enterprise-scale data solutions within a cloud-based environment. The successful candidate will play a key role in developing robust, scalable data pipelines and ensuring high standards of data quality, governance, and integration.
Role Overview
This role is best suited to an experienced engineer with a strong background in Informatica-based data engineering, complemented by hands-on experience across AWS and Azure data platforms. Working as part of a multidisciplinary delivery team, you will collaborate with architects, analysts, developers, and business stakeholders to deliver reliable and maintainable data solutions.
Key Responsibilities
- Data Pipeline Development
- Design, develop, and maintain robust ETL/ELT pipelines using Informatica and cloud-native technologies.
- Build scalable data ingestion, transformation, and delivery processes that support operational and analytical use cases.
- Cloud Data Engineering
- Develop and optimise data solutions across AWS and Azure platforms.
- Work with cloud services to improve scalability, resilience, and operational efficiency.
- Apply security best practices when managing data storage, processing, and access.
Essential Skills & Experience
- Informatica & Data Engineering (Primary Requirement)
- Extensive hands-on experience with Informatica.
- Proven track record delivering data engineering projects involving:
- ETL and ELT pipeline development
- Data integration and transformation
- Data quality management
- Enterprise data management practices
- Strong understanding of:
- Source-to-target mappings
- Data lineage
- Data validation and reconciliation
- Batch and scheduled processing
- Ability to design scalable, maintainable, and reusable data workflows.
- AWS Data Platform Experience (Essential)
- Strong practical experience with Amazon Web Services
- Familiarity with cloud-native data engineering services, including:
- S3 for storage
- Glue for ETL and cataloguing
- Redshift for analytics
- Lambda for event-driven processing
- Understanding of:
- IAM roles and permissions
- Security best practices
- Monitoring and operational considerations in AWS environments
- Experience designing and supporting data pipelines hosted on AWS infrastructure.
- Azure Data Platform Experience (Essential)
- Hands-on experience with Microsoft Azure in data engineering contexts
- Practical knowledge of services such as:
- Azure Data Factory
- Azure Synapse Analytics
- Comparable Azure-native data services
- Ability to work confidently across hybrid or multi-cloud data environments and understand the implications for integration, orchestration, and governance.
Collaboration & Technical Leadership
Partner with: Data Architects/ Business Analysts / Developers / Platform and Infrastructure teams. Translate business requirements into scalable technical solutions. Provide guidance and technical input to less experienced team members where appropriate.
Apply Now and help shape the future of UK digital services with Amber Labs.
Senior Data Engineer (Active SC Clearance Required) in London employer: Amber Labs
Amber Labs is an exceptional employer that champions innovation and collaboration in the digital consultancy space, particularly within the UK public sector. With a fully remote work model, employees enjoy flexibility while contributing to meaningful projects that drive digital transformation. The company fosters a supportive work culture that prioritises professional growth, offering opportunities for skill enhancement and career advancement in cutting-edge cloud and data technologies.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer (Active SC Clearance Required) in London
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We think you need these skills to ace Senior Data Engineer (Active SC Clearance Required) in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Amber Labs. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Amber Labs
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Amber Labs!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
