At a Glance
- Tasks: Design and maintain data engineering solutions for complex client needs.
- Company: Leading tech and digital intelligence organisation in Central London.
- Benefits: Competitive salary, hybrid working, and opportunities for professional growth.
- Other info: Join a dynamic team tackling complex data challenges with cutting-edge technology.
- Why this job: Lead innovative data projects and make a real impact in the public sector.
- Qualifications: Strong data engineering experience with Python, SQL, and AWS expertise.
The predicted salary is between 63000 - 77000 £ per year.
A leading technology and digital intelligence organisation is seeking an experienced Senior Data Engineer to design, develop and maintain data engineering solutions supporting complex client requirements, including work within the National Security and public sector environments.
The successful candidate will combine strong technical data engineering expertise with the ability to lead engineering teams, engage with stakeholders and translate business requirements into effective, scalable data solutions. Working alongside data architects, data scientists, analysts and wider technical teams, the Senior Data Engineer will help organisations extract, transform, store and deliver data for downstream consumption, enabling informed decision-making and improved business outcomes.
This is an opportunity for a technically accomplished data professional to take ownership of engineering delivery, shape data platforms and contribute to the development of modern data engineering practices.
Key Responsibilities
- Design, build, improve and maintain data pipelines and ETL processes to extract, transform and load data.
- Develop and deploy high-quality data engineering components using software engineering and DataOps best practices.
- Collaborate with data architects, data scientists, analysts and other engineering teams to deliver effective data flows.
- Develop and maintain cloud-based data infrastructure and services to host and store data.
- Apply data management, orchestration, security and data modelling principles across engineering solutions.
- Adapt to evolving data engineering tools, technologies and techniques.
- Lead data engineering teams from a technical perspective, establishing delivery frameworks that support effective execution.
- Lead technical design sessions and contribute to the selection of strategic data products for data engineering platforms.
- Develop broader expertise across data architecture, data strategy, data science, data modelling and analytics.
- Demonstrate increasing technical depth and breadth across a range of data engineering products and technologies.
Essential Skills & Experience
- Strong data engineering experience, combining hands-on technical capability with leadership and stakeholder engagement skills.
- Strong programming skills in Python, SQL or similar programming languages.
- Extensive experience with AWS.
- Experience building, maintaining and optimising data pipelines and ETL processes.
- Understanding of data engineering principles, data management and data modelling.
- Experience with data orchestration and the development of reliable data workflows.
- Experience establishing or working with cloud services to host data infrastructure and store data.
- Knowledge of data security and the principles required to manage data effectively.
- Experience applying software engineering practices to data development and deployment.
Senior-Level Technical Leadership
- Providing technical leadership to data engineering teams.
- Building effective teams and supporting collaboration across data disciplines.
- Developing expertise across data architecture, strategy, modelling and analytics.
Cloud Data Engineering & Data Platforms
- Configuring cloud services to support data infrastructure and storage requirements.
- Understanding how data is collected, processed, stored and made available to downstream consumers.
- Ability to work across different data engineering tools and platforms, assess technical options and select appropriate solutions for client requirements.
- Experience with modern data engineering approaches, orchestration, cloud infrastructure and DataOps practices.
- Exposure to complex data challenges and the opportunity to work with multidisciplinary teams developing high-quality technical solutions.
- Comfortable working collaboratively, understanding client needs and delivering data engineering outcomes within environments where technical quality and effective delivery are essential.
Security Clearance
Security Clearance is required for this position.
Senior Data Engineer - AI & Data in London employer: ANSON MCCADE
Anson McCade is an exceptional employer that prioritises employee well-being and professional growth, offering a flexible remote working environment in the UK. With a strong focus on security and digital transformation, employees benefit from comprehensive training programmes and clear pathways for career advancement, all while contributing to impactful projects alongside talented teams and senior stakeholders.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer - AI & Data in London
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like ANSON MCCADE.
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We think you need these skills to ace Senior Data Engineer - AI & Data 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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at ANSON MCCADE, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at ANSON MCCADE. 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 ANSON MCCADE
✨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!
✨Showcase Your Projects
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 ANSON MCCADE!
✨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.
