At a Glance
- Tasks: Lead the strategic direction of a cutting-edge data platform and manage a dynamic engineering team.
- Company: Join a leading organisation investing in innovative data capabilities.
- Benefits: Competitive salary up to £110,000 and fully remote work within the UK.
- Other info: Opportunity to collaborate with diverse teams and drive impactful business outcomes.
- Why this job: Shape the future of data engineering while influencing technical strategy across the organisation.
- Qualifications: Experience in modern data platforms and strong leadership skills.
The predicted salary is between 63000 - 77000 £ per year.
We are partnering with a leading organisation that is investing heavily into its data platform capability and is looking to appoint an experienced Platform Engineering Manager to lead the strategic direction of its snowflake environment. This is a fantastic opportunity for someone who enjoys sitting at the intersection of technology and business.
You will be responsible for ensuring the platform enables data engineering teams to deliver innovative, business-facing products, whilst influencing technical strategy and collaborating with stakeholders across the organisation. This isn't the opportunity for someone who wants to remain hands-on with coding, but someone who will be using their technical expertise.
Salary: Up to £110,000
Location: Fully Remote Within the UK
What you'll be doing:
- Leading technical strategy and roadmap for the snowflake platform
- Managing and developing a cross-functional platform engineering team
- Working closely with the data engineering teams, architects and engineers to enable successful product delivery
Key Skills:
- A deep understanding of modern data platforms and engineering principles
- The ability to influence technical direction without needing to be a hands-on developer
- Experience leading platforms or engineering teams and delivering business outcomes, rather than simply managing technology projects
- Excellent communication skills with the ability to build relationships across both technical and business functions
Platform Engineering Manager employer: Sanderson
At Sanderson, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of Belfast. Our commitment to employee growth is evident through tailored development programmes and opportunities for advancement, ensuring that our team members thrive in their careers while enjoying competitive rewards and a strong focus on health and safety compliance. Join us to take ownership of impactful projects and be part of a supportive environment that values your contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Platform Engineering Manager
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
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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 Sanderson.
✨Apply Directly through Our Website
When you find a suitable opening like Platform Engineering Manager at Sanderson, 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 Platform Engineering Manager
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 Sanderson, 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 Sanderson. 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 Sanderson
✨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 Sanderson!
✨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.
