At a Glance
- Tasks: Lead data product strategy and collaborate with stakeholders to launch successful products.
- Company: Join a top UK brand focused on innovation in data and technology.
- Benefits: Enjoy hybrid working with 3 days onsite in London and competitive pay.
- Why this job: Be part of a dynamic team driving data strategy and making a real impact.
- Qualifications: 5+ years in data product management, strong Azure knowledge, and ML experience required.
- Other info: Opportunity for mentorship and continuous improvement in a supportive environment.
The predicted salary is between 43200 - 72000 £ per year.
This range is provided by VIQU IT Recruitment. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
We’re partnered with one of the UK’s leading brands that are currently hiring for a Data Product Management Lead. Our client is driven to be the best in the field and outdo with their experience in data and technology. The business has modified the work structure to help the customers, take on new technologies and develop business outclass.
The Data Product Management Lead will focus on the data and machine learning products and aim to drive the data strategy, development and delivery of the organisation. The position will benefit from hybrid working of 3 days a week onsite from their London office.
Responsibilities of the Data Product Management Lead:
- Drive the Data Product strategy that aligns with the business data strategy and goals.
- Collaborate with stakeholders at different levels to identify opportunities and make sure the product is launched successfully.
- Own the full lifecycle of the data products, governance to maintain quality, integrity and consistency of the products.
- Track the data product performance to drive continuous improvement.
Requirements of the Data Product Management Lead:
- 5+ years’ experience in Data product management with a background delivering data products.
- Experience managing and establishing governance.
- Strong understanding of Azure and related products including strong expertise of Databricks.
- Experience working in the insurance industry.
- Good background in Machine Learning (ML) analytics and deploying products.
- Proven ability to mentor teams and lead continuous improvement in the data environment.
- Excellent communication skills, attention to detail and self-starter.
To discuss this exciting opportunity in more detail, please APPLY NOW for a no obligation chat with your VIQU Consultant.
London (Hybrid)
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Strategy/Planning and Product Management
Industries
Data Infrastructure and Analytics, Insurance, and IT System Data Services
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Contact Detail:
VIQU IT Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Product Management Lead
✨Tip Number 1
Familiarise yourself with the latest trends in data product management, especially in the insurance sector. Understanding how data products are evolving in this industry will help you speak confidently about your insights during interviews.
✨Tip Number 2
Network with professionals who are currently working in data product management roles, particularly those with experience in Azure and Databricks. Engaging in conversations can provide you with valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss specific examples of how you've driven data product strategies in your previous roles. Highlighting your achievements in improving product performance and governance will demonstrate your capability for this position.
✨Tip Number 4
Showcase your leadership skills by discussing how you've mentored teams in the past. This is crucial for the Data Product Management Lead role, so be ready to share stories that illustrate your ability to foster continuous improvement.
We think you need these skills to ace Data Product Management Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data product management, particularly focusing on your 5+ years of relevant experience. Emphasise your background in delivering data products and any specific achievements in the insurance industry.
Craft a Compelling Cover Letter: Write a cover letter that showcases your understanding of the role and the company’s goals. Mention your expertise in Azure, Databricks, and machine learning analytics, and how these skills can contribute to driving the data strategy.
Highlight Leadership Skills: In your application, be sure to mention your ability to mentor teams and lead continuous improvement initiatives. Provide examples of how you've successfully collaborated with stakeholders to launch products.
Showcase Communication Skills: Since excellent communication is a requirement for this role, include instances where your communication skills have led to successful project outcomes. This could be in the form of presentations, reports, or stakeholder engagement.
How to prepare for a job interview at VIQU IT Recruitment
✨Understand the Data Product Lifecycle
Make sure you can discuss the full lifecycle of data products, from conception to delivery. Be prepared to share examples of how you've managed product governance and maintained quality in your previous roles.
✨Showcase Your Technical Expertise
Since the role requires strong knowledge of Azure and Databricks, brush up on these technologies. Be ready to explain how you've used them in past projects, especially in relation to machine learning analytics.
✨Demonstrate Stakeholder Collaboration
Prepare to talk about your experience working with various stakeholders. Highlight specific instances where you identified opportunities and successfully launched products by collaborating across different levels of the organisation.
✨Highlight Your Leadership Skills
As a Data Product Management Lead, you'll need to mentor teams and drive continuous improvement. Share examples of how you've led teams in the past, focusing on your ability to inspire and implement change effectively.