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: Enjoy remote work flexibility, competitive salary, and opportunities for professional growth.
- Other info: Collaborate with a multidisciplinary team and lead technical initiatives in a dynamic environment.
- Why this job: Make a real impact by developing scalable data solutions that drive digital transformation.
- Qualifications: Experience with Informatica, AWS, and Azure data platforms is essential.
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 Slough employer: Amber Labs
Amber Labs is an exceptional employer that champions innovation and collaboration in a fully remote environment, allowing you to work from anywhere while contributing to impactful digital transformation projects within the UK public sector. With a strong focus on employee growth, we offer opportunities for professional development and technical leadership, ensuring that our team members are equipped with the latest skills in cloud and data engineering. Join us to be part of a forward-thinking culture that values security, governance, and the pursuit of excellence in delivering data solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer (Active SC Clearance Required) in Slough
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We think you need these skills to ace Senior Data Engineer (Active SC Clearance Required) in Slough
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!
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✨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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✨Get Comfortable with Python and R
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✨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.
