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- Tasks: Join a 10-week paid fellowship to become a data engineer through hands-on training and real projects.
- Company: iO Sphere helps individuals master data and AI skills, connecting them with top UK employers.
- Benefits: Enjoy paid training, ongoing mentorship, and networking opportunities in a supportive community.
- Why this job: Gain valuable experience while working on real data projects and building essential skills for your career.
- Qualifications: No prior experience needed; just bring your curiosity and commitment to learn.
- Other info: We encourage applications from diverse backgrounds and offer scholarships for those in need.
The predicted salary is between 42000 - 84000 £ per year.
iO-Sphere's Data Engineering Fellowship is a 10-week paid training programme designed to help individuals secure a job as a data engineer. The Experience Accelerator connects trainees with leading employers in the UK, having successfully placed over 150 graduates in companies like Uber, Bumble, British Airways, Love Holidays, Dunelm, and Capgemini.
During the fellowship, you will be part of a fictional e-commerce company, "Prism," where you will gain hands-on experience while learning essential technical (Excel, SQL, Power BI, Python), professional, and business skills. You will work on real projects using a data warehouse with over 500 million rows of actual data.
The programme aims to support diversity in data and prioritises candidates from disadvantaged backgrounds. Selected fellows receive financial support throughout their training and access to various bursaries and scholarships.
How it works:
- Apply on our site - the application process takes only 30 seconds.
- Receive comprehensive training to become an effective data engineer, along with a stipend for support during training.
- iO-Sphere partners with leading employers to recruit directly from the programme.
- Upon graduation, you join the iO-Sphere community with ongoing support, mentoring, and networking events.
What we are looking for:
- Collaborative team players
- Numerate, analytical thinkers
- Curious problem solvers
- Humble and willing to learn
- Ability to commit to full-time for 10 weeks
- Fluent in written and spoken English
- Right to work in the United Kingdom
Programme expectations:
- An initial full-time 10-week training programme to develop technical skills, business acumen, soft skills, and practical experience.
- The first 5 weeks are full-time and fully remote; the final 5 weeks are full-time and in-person on Mondays, Thursdays, and Fridays.
- Ongoing mentorship and support after securing a role, including networking events, 1:1 mentorship from experts, further training, and social activities.
We strongly encourage applications from women, people of colour, LGBTQ+ individuals, veterans, parents, and individuals with disabilities. We are committed to equal opportunities and welcome individuals from all backgrounds to participate in our programme. If you require reasonable adjustments at any stage of the application or interview process, please inform us.
Data Engineering Fellowship employer: IO Sphere
Contact Detail:
IO Sphere Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering Fellowship
✨Tip Number 1
Familiarise yourself with the key technical skills mentioned in the job description, such as Excel, SQL, Power BI, and Python. Consider working on small projects or online courses that allow you to demonstrate your proficiency in these areas.
✨Tip Number 2
Engage with the iO Sphere community on social media platforms. Networking with current fellows and alumni can provide valuable insights into the programme and help you understand what they look for in candidates.
✨Tip Number 3
Prepare for potential interviews by practising common data engineering interview questions. Focus on problem-solving scenarios and be ready to discuss how you would approach real-world data challenges.
✨Tip Number 4
Showcase your curiosity and willingness to learn during any interactions with the iO Sphere team. Ask insightful questions about the fellowship and express your enthusiasm for developing your skills in data engineering.
We think you need these skills to ace Data Engineering Fellowship
Some tips for your application 🫡
Understand the Programme: Familiarise yourself with iO Sphere's Data Engineering Fellowship. Highlight your understanding of the programme's structure, including the 10 weeks of paid training and the skills you'll acquire.
Tailor Your CV: Make sure your CV reflects relevant skills and experiences related to data engineering. Emphasise any technical skills like Excel, SQL, Power BI, or Python that align with the job requirements.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data and your eagerness to learn. Mention why you are interested in the fellowship and how it aligns with your career goals.
Highlight Diversity and Inclusion: If applicable, share your background and experiences that resonate with iO Sphere's commitment to diversity. This can strengthen your application and show that you align with their values.
How to prepare for a job interview at IO Sphere
✨Show Your Curiosity
During the interview, demonstrate your curiosity about data engineering. Ask insightful questions about the projects you'll be working on and the technologies used at iO Sphere. This shows that you're genuinely interested in the role and eager to learn.
✨Highlight Relevant Skills
Make sure to emphasise any technical skills you possess that are relevant to the role, such as SQL, Python, or Excel. Even if you’re still learning, discussing your progress and how you plan to apply these skills can impress the interviewers.
✨Emphasise Teamwork
Since the role requires collaboration, share examples of past experiences where you worked effectively in a team. Highlight your ability to communicate and solve problems collectively, which aligns with the values of iO Sphere.
✨Prepare for Scenario Questions
Be ready to tackle scenario-based questions that assess your problem-solving abilities. Think of examples where you've faced challenges and how you approached them, especially in data-related contexts. This will showcase your analytical thinking and adaptability.
