At a Glance
- Tasks: Develop and maintain data products while building cloud-based data solutions on Azure.
- Company: Join Nest, a leading organisation in the pension sector with a commitment to innovation.
- Benefits: Enjoy flexible working, competitive bonuses, and a generous pension scheme.
- Other info: Dynamic work environment with opportunities for personal growth and development.
- Why this job: Be part of a transformative journey using data to drive impactful decisions for millions.
- Qualifications: Experience in data engineering and a passion for analytics are key.
The predicted salary is between 28800 - 48000 £ per year.
Overview
Data Engineer role at Nest Pensions. You’ll work with stakeholders to develop, test, and maintain data products and solutions that align with their requirements. You’ll develop a cloud-based data and analytics platform on Azure and help end-users integrate their workflows between this and other platforms, including AWS-based solutions. You’ll combine data from different sources and build data pipelines to transform and organise raw data into formats that can be easily used for business intelligence as well as deep dive analysis and modelling.
Role details
Interviews will be face to face in the London office. We are open to discussing working patterns. We welcome all internal applicants to apply for our roles, regardless of current working pattern or hours, and we will aim to accommodate your current arrangements. If you think you don’t have all key skills, it may be worth applying as we’re good at spotting potential and offer a generous training budget. Please download a full job description to see the full scope, deliverables, experience and personal attributes required for this role.
Responsibilities
- Develop, test, and maintain data products and solutions that align with stakeholder requirements.
- Develop a cloud-based data and analytics platform on Azure.
- Help end-users integrate workflows between the Azure platform and other platforms, including AWS-based solutions.
- Combine data from different sources and build data pipelines to transform and organise raw data for business intelligence and modelling.
Qualifications
- Experience as a Data Engineer or similar role.
- Experience with Azure data services and building data pipelines.
- Knowledge of ETL/ELT, data modelling, and data governance.
- Strong collaboration with stakeholders.
Benefits
- A discretionary bonus scheme
- Reward and recognition scheme
- Enhanced auto enrolled pension – your contributions start at the default 5% while ours are higher at 8%. If you increase your contributions to 6% we raise ours to 9%. If you contribute 7% or more we’ll contribute 10%.
- Income protection scheme – provides income if you cannot work due to illness or incapacity.
Working pattern
- Hybrid of office (Canary Wharf, London) and home working (attendance at the office may be required once or more per week as needed).
- Flexible options including reduced hours, reduced days, compressed hours, or job share.
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Data Engineer in London employer: Nest Pensions
Nest Pensions is an excellent employer that fosters a collaborative and innovative work culture, particularly in the vibrant city of London. With a strong focus on employee growth, we offer numerous opportunities for professional development and training in technology and data risk management. Our commitment to regulatory compliance and a robust risk culture ensures that you will play a vital role in safeguarding our organisation while enjoying the benefits of a hybrid working model.
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We think you need these skills to ace Data Engineer in London
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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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✨Brush Up on Your Statistics
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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.
