At a Glance
- Tasks: Develop innovative data-driven solutions and automate data engineering pipelines.
- Company: Join a leading UK client with a focus on data security and customer value.
- Benefits: Flexible remote work, competitive salary, and a 10% benefit-as-cash.
- Other info: Work from Edinburgh, London, or Manchester with excellent career growth opportunities.
- Why this job: Make an impact by simplifying data processes and driving customer success.
- Qualifications: Experience in ETL design, AWS platforms, SQL, and Python required.
The predicted salary is between 63000 - 77000 £ per year.
We are collaborating in sourcing several Data Engineers for a large UK client. You will work from your choice of the Edinburgh, London or Manchester offices, with 6 days per month working in the office, and the rest remotely.
What you'll do - As a Data Engineer, you'll be looking to simplify our organisation by developing innovative data-driven solutions through data pipelines, modelling and ETL design, aiming to be commercially successful while keeping our customers and the bank’s data safe and secure. You'll drive customer value by understanding complex business problems and requirements to correctly apply the most appropriate and reusable tool to gather and build data solutions. You'll support our strategic direction by engaging with the data engineering community to deliver opportunities, along with carrying out complex data engineering tasks to build a scalable data architecture.
Your responsibilities will also include:
- Building advanced automation of data engineering pipelines through removal of manual stages
- Embedding new data techniques into our business through role modelling, training, and experiment design oversight
- Delivering a clear understanding of data platform costs to meet your department's cost-saving and income targets
- Sourcing new data using the most appropriate tooling for the situation
- Developing solutions for streaming data ingestion and transformations in line with our streaming strategy
The skills you'll need:
- Strong understanding of data usage and dependencies and experience of extracting value and features from large-scale data.
- Experience designing ETL and ELT solutions, delivering high-quality, well-modelled data through rigorous testing, cleansing, monitoring, and modern data warehousing on platforms such as Snowflake
- Hands-on experience with AWS cloud data platforms and managed services, including S3 object storage, Airflow, QuikSight, managed ETL, using AWS Glue and metadata services, along with strong security and governance practices
- Experience of using programming languages like SQL and Python, alongside knowledge of data and software engineering fundamentals
- Good knowledge of modern code development practices
- Strong communication skills with the ability to proactively engage with a wide range of stakeholders
SALARY INCLUDES 10% BENEFIT-AS-CASH
Data Engineer (EDI) employer: McNally Recruitment Ltd
As an Infrastructure Engineer with our Financial Services company, you will thrive in a dynamic work culture that prioritises innovation and collaboration. With offices in both Edinburgh and London, we offer flexible working arrangements and a commitment to employee growth through continuous learning opportunities. Join us to be part of a forward-thinking team that values your expertise in building resilient cloud solutions while enjoying the unique advantages of working in the vibrant financial sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (EDI)
✨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 McNally Recruitment Ltd.
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We think you need these skills to ace Data Engineer (EDI)
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 McNally Recruitment Ltd, 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 McNally Recruitment Ltd. 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 McNally Recruitment Ltd
✨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 McNally Recruitment Ltd!
✨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.
