At a Glance
- Tasks: Design and maintain data pipelines, ensuring high-quality data for critical business decisions.
- Company: A leading tech consultancy with a collaborative and empowering culture.
- Benefits: Competitive salary, professional development, and opportunities for growth.
- Other info: Exciting career growth opportunities in a fast-paced environment.
- Why this job: Join a dynamic team and tackle complex challenges with cutting-edge technology.
- Qualifications: Experience in data engineering, SQL, Python, and AWS required.
The predicted salary is between 63000 - 77000 £ per year.
About the Company
While professional experience and qualifications are key for this role, make sure to check you have the preferable soft skills before applying if required.
Our client is a specialist technology consultancy delivering tailored solutions across financial services, private capital, and defence sectors.
Established through a partnership between leading global organisations, the business combines deep industry expertise with cutting-edge technology to solve complex challenges for its clients.
The company promotes a collaborative, trust-based culture where employees are empowered to take ownership of their work, develop their skills, and make a meaningful impact.
With its headquarters in Newcastle upon Tyne and a growing international presence, the organisation is continuing to expand its capabilities and team.
Company Culture
The organisation is seeking talented professionals who
- Demonstrate strong communication and collaboration skills.
- Enjoy working closely with colleagues and business stakeholders to achieve shared goals.
- Are naturally curious and motivated to explore new ideas and technologies.
- Thrive in fast-paced environments, tackling complex challenges with creativity and enthusiasm.
- Take ownership of their work and consistently deliver high-quality outcomes.
- Have a strong desire to learn, grow, and develop professionally.
The Opportunity
An exciting opportunity has arisen for a Data Engineer to join a high-performing Data Analytics team.
The successful candidate will play a key role in designing, developing, and maintaining data solutions that support critical business and investment activities.
Key Responsibilities
- Design, build, and maintain robust data pipelines that integrate data from external vendors, market counterparties, and other sources into a centralised data platform.
- Contribute to the enhancement and evolution of the firm's data platform, ensuring it continues to meet changing business needs.
- Perform testing, monitoring, and troubleshooting to maintain platform performance and reliability.
- Ensure data is accurate, accessible, and of high quality, supporting business-critical decision-making processes.
- Work closely with internal stakeholders to improve data availability, usability, and overall platform effectiveness.
- Support continuous improvement initiatives through the adoption of modern data engineering tools, technologies, and best practices.
- Candidate Requirements
- Applications are welcomed from candidates across a range of experience levels.
- Strong experience designing, developing, and maintaining data pipelines.
- Proficiency in SQL, Python, AWS, and other modern data engineering technologies. xsabvtc
- Experience with version control tools (e. g., Git) and workflow orchestration platforms (e. g., Airflow).
Data Developers employer: Harvey Nash Careers
As a Lead Architect, you will join a forward-thinking organisation at the heart of the UK's critical infrastructure transformation. With a strong focus on employee development, competitive benefits including a robust pension and medical coverage, and a collaborative work culture, this role offers a unique opportunity to make a meaningful impact while advancing your career in a dynamic environment. Located in North East England or Yorkshire, you'll be part of a team that values innovation and excellence, driving significant change across essential services.
StudySmarter Expert Advice🤫
We think this is how you could land Data Developers
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Harvey Nash Careers!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Developers at Harvey Nash Careers.
✨Leverage Professional Networks
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 Harvey Nash Careers.
✨Apply Directly through Our Website
When you find a suitable opening like Data Developers at Harvey Nash Careers, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Developers
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 Harvey Nash Careers, 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 Harvey Nash Careers. 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 Harvey Nash Careers
✨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 Harvey Nash Careers!
✨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.
