At a Glance
- Tasks: Lead and transform the analytics engineering programme while managing a talented team.
- Company: Join Bumble Inc., a fast-paced tech company focused on fostering kind connections.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and drive innovation across multiple brands.
- Why this job: Make a real impact by shaping data strategies in a dynamic environment.
- Qualifications: Experience in analytics engineering and strong leadership skills required.
The predicted salary is between 80000 - 100000 £ per year.
This role will develop the analytics engineering programme and the capabilities across the analytics organisation. They will work to train, hire, and manage the performance of the team, tools, and standards put into place. This is a unique opportunity for an established analytics engineering leader who enjoys the fast paced environment of a growing company, has vast experience in analytics engineering and has a passion to lead teams helping the Bumble Inc. mission to foster kind connections. You would ideally have a background in analytics engineering at either a dating, social, gaming or other relevant tech company, with proven experience of driving data quality, sources of truth, KPI alignment, and optimisation of data warehouse consumption costs. You understand the high-level business model of the company and its primary drivers to build strategies and teams that respond to ever changing business needs. You will help senior leadership across tech and the business navigate ambiguity and shape analytical roadmaps, projects and insights briefs. You bring experience of working with large multi-disciplined analytics teams and complex data sources. You will be fluent in a range of analytical and engineering techniques from data modelling and governance, quality, reliability, and scalability, self-serve analytics, to onboarding and overhauling data stacks with new vendor solutions. Internally, this role is known as Associate Director, Analytics Engineering.
KEY ACCOUNTABILITIES
- Transform the analytics organisation to onboard the analytics engineering capability, whilst leading, shaping, and hiring a team of analytics engineers.
- Onboard analytics engineering tools and rolling out with the relevant talent and standards across decentralised organisations.
- Set up best practices around data governance, quality, observability, and lineage.
- Run a hybrid model of analytics engineers embedded across a large multi-domain organisation while managing partnership with business stakeholders, data science, and data engineering.
- Create a data dictionary, business-wide metric and taxonomy alignment which reflects the data mart infrastructure.
- Enforce governance standards across non-technical analysts to manage consumption costs and efficiencies of queries.
- Lead teams to create enterprise level reporting solutions that align stakeholders and feed into external reporting procedures around a common source of truth.
- Run an RFP process and rollout of an enterprise visualisation solution.
- Own the business data model design and ownership distribution as well as best practices around tooling, maintenance, and incident management.
- Own the analytics engineering roadmap and be able to flex resource as required.
- Scale strategic initiatives which benefit all brands by creating fungible resourcing distributed by skill and capability.
- Set and track OKRs for the data programme at large, with a focus on quality, reliability, speed, and accessibility.
REQUIRED EXPERIENCE & SKILLS
- Preference for a graduate degree in Mathematics, Engineering, Information Sciences, Economics, Finance, or STEM. PhD and Masters welcome.
- Preference for experience working in similar dating/social/gaming tech product industries or else financial services/high-data-volume industries.
- You will have had ample experience working with a large distributed team of analysts and analytics engineers and across multiple brands and levels.
- You will have rolled out an analytics engineering programme in a large enterprise before, showing success and impact to the data quality and ROI.
- You will have on-boarded data tooling across the entire data value chain and are familiar with different combinations of vendors, their optimal ways of integrating with each other, and are able to advise on the commercial agreements, RFPs, and onboarding processes across timelines, domains, and brands.
- You have established partnerships and relationships with the most relevant vendors.
- You will have led an enterprise-wide data clean-up before, re-establishing reporting, sources of truth, KPI alignment, and a dashboarding ecosystem relevant for all stakeholders.
- You have ample experience architecting a distributed analytics engineering programme, knowing how to manage competency frameworks, training, and distributed ownership of a decentralised data mart network.
- You have experience working with complex data infrastructures and have experience partnering and guiding the work of data engineering to help facilitate ingestion, warehousing, and optimisation of databases.
- You have made established partnerships with engineering to help drive data collection quality.
- 5+ years experience in leading analytics engineering, data engineering, or automation teams, working in a fast paced environment.
ABOUT YOU
- Strong believer in Bumble Inc.’s brand vision and values.
- Engaging, inspiring and clear communicator.
- A proven track record of overhauling data landscapes and engaging stakeholders to get their buy-in.
- Strong automation and growth mindset that is cascaded to the teams.
- Deep engineering and data infrastructure understanding of both 3rd party vendors and bespoke in-house solutions.
- Experience in guiding the planning and prioritisation efforts of your teams in a busy and fast moving environment.
- Experience working with legal, infosec, and 3rd party vendors, understanding how to maximise these relationships to drive value for the team.
- Experience with python/SQL, visualisation tooling such as Looker/Tableau, and data stack tooling across transformation, collection, and data science.
- Strong experience with driving ROI of an analytics programme.
- Strong governance and data quality mindset.
- Understands and can demonstrate machine learning and advanced analytical product impact in an organisation.
Product Analytics Manager - Other Brands (FTC) employer: Bumble
Bumble Inc. is an exceptional employer that fosters a dynamic and inclusive work culture, perfect for those passionate about analytics engineering. With a commitment to employee growth, you will have the opportunity to lead and shape a talented team while driving impactful data initiatives in a fast-paced environment. Located in a vibrant tech hub, Bumble offers unique advantages such as collaboration with diverse brands and access to cutting-edge tools, ensuring your contributions are both meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Product Analytics Manager - Other Brands (FTC)
✨Tip Number 1
Network like a pro! Reach out to folks in the analytics engineering space, especially those who work at companies you admire. A casual chat can lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your past projects and achievements in analytics engineering. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common analytics engineering challenges. Be ready to discuss how you've tackled data quality issues or optimised data warehouse costs in your previous roles.
✨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 about their job search!
We think you need these skills to ace Product Analytics Manager - Other Brands (FTC)
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience in analytics engineering. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects or achievements!
Showcase Your Leadership Skills:Since this role involves leading a team, it’s crucial to demonstrate your leadership experience. Share examples of how you've managed teams, driven initiatives, or improved processes in your previous roles. We love seeing candidates who can inspire and motivate others!
Be Clear and Concise:When writing your application, keep it straightforward and to the point. Use clear language and avoid jargon unless it's necessary. We appreciate candidates who can communicate complex ideas simply and effectively!
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts and you’ll be set!
How to prepare for a job interview at Bumble
✨Know Your Analytics Engineering Inside Out
Make sure you brush up on your analytics engineering knowledge. Be ready to discuss your experience with data modelling, governance, and quality. Prepare examples of how you've driven data quality and optimised data warehouse costs in previous roles.
✨Showcase Your Leadership Skills
This role requires strong leadership capabilities. Think about times when you've successfully led a team or project. Be prepared to share how you managed performance, trained team members, and navigated ambiguity while aligning stakeholders.
✨Familiarise Yourself with the Company’s Mission
Understand Bumble Inc.'s mission to foster kind connections. Be ready to explain how your values align with theirs and how you can contribute to their goals through your analytics expertise.
✨Prepare for Technical Questions
Expect technical questions related to data tools and vendor solutions. Brush up on your knowledge of Python, SQL, and visualisation tools like Looker or Tableau. Be ready to discuss how you've onboarded data tooling and managed complex data infrastructures.
