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- Tasks: Own data implementation and validation while supporting payments analysis.
- Company: Join a leading IT services company focused on innovation.
- Benefits: Competitive pay, flexible work options, and opportunities for growth.
- Why this job: Make an impact by developing scalable solutions in a dynamic environment.
- Qualifications: 3–5 years in data analytics, strong SQL, PySpark, and Python skills.
- Other info: Collaborative culture with a focus on professional development.
The predicted salary is between 36000 - 60000 £ per year.
Data Engineer/Analyst – 12 month contract – Fintech/Analytics – Hybrid (2 days London) – Inside IR35
The chosen candidate will own PySpark table implementation, business logic translation, and data validation. They will also support payments analysis, improve data infrastructure, and develop scalable solutions to meet evolving needs.
Overview:
3–5 years in data analytics and visualization
Industry experience with big data projects
Strong SQL and PySpark skills
Proficient in Python
Experience with large datasets and data pipelines
Familiar with big data tools and version control (e.g., Git)
Knowledge of financial metrics (a plus)
Strong communication and stakeholder skills
Detail-oriented with strategic thinking
Data Engineer/Analyst employer: Halian | Managed Services, Recruitment Agency & Contract Staffing
Contact Detail:
Halian | Managed Services, Recruitment Agency & Contract Staffing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer/Analyst
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential employers on LinkedIn. You never know who might have the inside scoop on a job opening!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving SQL and PySpark. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding of big data tools. Practice common interview questions related to data analytics and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team directly.
We think you need these skills to ace Data Engineer/Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data analytics and visualisation. We want to see your SQL and PySpark skills shine, so don’t hold back on showcasing relevant projects you've worked on!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for the Data Engineer/Analyst role. Share specific examples of how you've tackled big data projects and improved data infrastructure in the past.
Show Off Your Technical Skills: We love seeing strong technical skills! Be sure to mention your proficiency in Python and any experience with big data tools or version control like Git. This will help us understand your capabilities right off the bat.
Apply Through Our Website: To make sure your application gets the attention it deserves, apply directly through our website. It’s the best way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Halian | Managed Services, Recruitment Agency & Contract Staffing
✨Know Your Data Inside Out
Make sure you brush up on your SQL and PySpark skills before the interview. Be ready to discuss specific projects where you've implemented these technologies, as well as any challenges you faced and how you overcame them.
✨Showcase Your Big Data Experience
Prepare examples of your work with large datasets and data pipelines. Highlight any big data tools you've used and how they contributed to the success of your projects. This will demonstrate your hands-on experience in the field.
✨Communicate Clearly and Confidently
Since strong communication skills are essential for this role, practice explaining complex data concepts in simple terms. Think about how you would present your findings to stakeholders who may not have a technical background.
✨Be Detail-Oriented and Strategic
During the interview, emphasise your attention to detail and strategic thinking. Discuss how you've approached data validation and business logic translation in past roles, and be prepared to share your thought process behind these tasks.
