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- Tasks: Lead the development of a cutting-edge data platform and mentor your team.
- Company: A top parking solutions provider in Greater London with a focus on innovation.
- Benefits: Competitive salary and a comprehensive benefits package.
- Why this job: Shape the future of data solutions and make a real impact in the industry.
- Qualifications: 8-10 years of experience with dbt, BigQuery, SQL, and Python.
- Other info: Join a dynamic team and contribute to exciting data initiatives.
The predicted salary is between 54000 - 84000 £ per year.
A leading parking solutions provider in Greater London is seeking a Data Platform Lead to own and develop its data platform. This position demands 8-10 years of experience with dbt and BigQuery, strong skills in SQL and Python, and expertise in data modeling.
The role involves mentoring team members and overseeing data initiatives to ensure scalability and reliability. The ideal candidate will integrate ML outputs and contribute to the long-term architectural vision of the platform. A competitive benefits package is provided.
Data Platform Lead: Scale Pipelines & Insights in London employer: Justpark
Contact Detail:
Justpark Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Platform Lead: Scale Pipelines & Insights in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work with dbt, BigQuery, SQL, and Python. This could be a GitHub repo or a personal website. It’s a great way to demonstrate your expertise and make you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data platform challenges and solutions. Think about how you would approach scalability and reliability in your projects. We want to see you shine when discussing your experience and vision!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive and engaged with our company.
We think you need these skills to ace Data Platform Lead: Scale Pipelines & Insights in London
Some tips for your application 🫡
Show Off Your Experience: Make sure to highlight your 8-10 years of experience with dbt and BigQuery. We want to see how your skills in SQL and Python have shaped your career, so don’t hold back on those details!
Be Specific About Your Skills: When you mention your expertise in data modeling, give us examples of projects you've worked on. We love seeing how you've tackled challenges and contributed to data initiatives in the past.
Mentorship Matters: Since this role involves mentoring team members, share any experiences you've had in guiding others. We’re keen to know how you’ve helped your colleagues grow and succeed in their roles.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves!
How to prepare for a job interview at Justpark
✨Know Your Tech Inside Out
Make sure you brush up on your dbt and BigQuery skills before the interview. Be ready to discuss specific projects where you've used these tools, as well as any challenges you faced and how you overcame them.
✨Show Off Your SQL and Python Prowess
Prepare to demonstrate your SQL and Python knowledge with practical examples. Think of scenarios where you've optimised queries or automated processes, and be ready to explain your thought process.
✨Mentorship Matters
Since this role involves mentoring, think about your past experiences in guiding team members. Have a couple of anecdotes ready that showcase your leadership style and how you've helped others grow in their roles.
✨Think Long-Term
The job requires contributing to the long-term architectural vision of the platform. Be prepared to discuss your views on data architecture trends and how you would approach integrating ML outputs into the existing framework.
