Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead the development of innovative data products and collaborate with analytics teams.
- Company: Join Greystar, a global leader in real estate with a focus on equality and diversity.
- Benefits: Enjoy competitive pension, healthcare, and generous holiday allowance.
- Why this job: Make a real impact by shaping data strategies and driving business value.
- Qualifications: 5+ years in data roles, strong SQL and Python skills, and Agile experience.
- Other info: Dynamic work environment with opportunities for professional growth and global reach.
The predicted salary is between 60000 - 80000 £ per year.
The Data Product position is accountable for defining, governing, and evolving domain-aligned data products in alignment with Greystar’s data strategy. Partnering closely with Data Engineers and Architects, this role ensures that data products built are architecturally aligned, properly modelled, governed, scalable, and usable across the organization. You will act as the primary point of contact for Line of Business (LOB) analytics teams, define roadmaps and priorities, translate business requirements into actionable data product features and enable self-service analytics by ensuring business teams can use curated data assets. While you will not build pipelines, you are technically fluent in how data pipelines, ingestion patterns, and dimensional models operate within a modern lakehouse architecture.
Key Responsibilities
- Define grain, primary keys, and conformed dimensions for gold-layer data products.
- Author detailed source-to-target mappings across bronze → silver → gold transformations.
- Partner with engineering on normalized vs dimensional modelling trade-offs.
- Validate modelling strategy (SCD types, surrogate keys, etc).
- Define data contracts between upstream ingestion pipelines and downstream consumers.
- Serve as the primary point of contact for the analytics teams they support.
- Define and manage the roadmap and priorities for data initiatives in partnership with analytics leaders.
- Provide updates on backlog progress, risks, dependencies, and timelines to stakeholders.
- Own and prioritize the Data Marketplace (DMP) backlog in alignment with engineering capacity, business needs and architectural constraints.
- Translate business requirements into transformation logic, schema changes, acceptance criteria, and data quality rules.
- Balance feature delivery with platform stability and technical debt considerations.
- Perform testing and validation to ensure acceptance criteria is met and data deployed to production is of high quality and able to drive business value.
- Ensure consistency of business rules and data definitions across multiple LOBs; coordinate with Governance to resolve misalignments.
- Ensure governance requirements (RBAC, PII masking, compliance controls) are embedded into data products.
- Surface and escalate conflicting business requirements to governance teams, helping drive consensus.
- Support root-cause analysis of data defects in partnership with engineering.
- Use SQL and Python to support just-in-time analysis and prototyping for the analytics teams.
- Develop lightweight prototypes demonstrating gold dataset usability.
- Ensure datasets are analytics-ready and optimized for Power BI / enterprise consumption.
- Drive reuse of shared enterprise assets instead of LOB-specific duplications.
- Facilitate resolution of conflicting business rules with governance teams.
- Communicate and answer questions about upcoming releases and articulate business values the changes will enable.
About You
You bring 5+ years of experience across Data Product, Data Architecture, Analytics Engineering or similar data-focused roles, combined with strong organisational skills and hands-on Agile delivery experience. You are confident managing stakeholders and translating complex technical concepts into clear business outcomes. With advanced SQL skills and working knowledge of Python, you understand dimensional modelling, data normalisation, and batch ETL design, including schema evolution. You are comfortable working with modern data platforms such as Databricks, Snowflake and Azure Data Factory, and have a solid grasp of enterprise data governance and data quality best practices.
What We Offer
We include a range of benefits for our corporate team members, including competitive pension, healthcare, and holiday allowance, amongst others as standard. Please reach out if you are keen to know more.
About Greystar
Greystar is a leading, fully integrated real estate company offering expertise in investment management, development, and management of rental housing properties globally. The company's business model is unique in its ability to own, operate, and develop multifamily, student, and senior housing across the globe. Building a global platform with a local presence, Greystar continues to expand its geographic reach around the world, bringing a globally interconnected professional rental housing platform and industry funded with institutional capital to countries where the sector does not yet exist. Greystar’s pan-European platform was established in 2013 and has scaled rapidly, now with investment, operational and development presence in the UK, Ireland, France, the Netherlands, Germany, Austria, and Spain.
One of Greystar’s core values is Equality, and as such, we continue to pride ourselves on being an equal opportunities employer, accounting for all protected and identifiable characteristics. We truly value diversity of thought, background and of experience. Please reach out to the Talent Acquisition team to explore opportunities at Greystar in more detail or visit our careers site.
Data Product Lead/Engineer in London employer: Greystar (International)
Contact Detail:
Greystar (International) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Product Lead/Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or a GitHub repository showcasing your projects. This gives potential employers a taste of what you can do, especially in data product roles.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to data products. Think about how you’d explain complex concepts simply – it’s all about clear communication!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Product Lead/Engineer in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience in data product management and analytics. We want to see how your skills align with the specific responsibilities mentioned in the job description.
Showcase Your Technical Skills: Don’t forget to emphasise your SQL and Python expertise! Mention any relevant projects or experiences that demonstrate your ability to work with data pipelines and dimensional modelling, as these are key for the role.
Be Clear and Concise: When writing your application, keep it straightforward and to the point. Use bullet points where possible to make it easy for us to read through your qualifications and achievements.
Apply Through Our Website: We encourage you to submit your application directly through our careers site. This way, you’ll ensure it reaches the right people and you can easily track your application status!
How to prepare for a job interview at Greystar (International)
✨Know Your Data Products
Before the interview, make sure you understand the key concepts of data products, especially in relation to Greystar’s data strategy. Brush up on how to define grain, primary keys, and conformed dimensions, as well as the importance of data governance and quality.
✨Showcase Your Technical Fluency
Be prepared to discuss your experience with SQL and Python, particularly in the context of data modelling and ETL processes. Highlight any projects where you've worked with modern data platforms like Databricks or Snowflake, and be ready to explain how you’ve used these tools to drive business value.
✨Communicate Clearly with Stakeholders
Since this role involves acting as a primary point of contact for analytics teams, practice articulating complex technical concepts in simple terms. Think of examples where you successfully managed stakeholder expectations and translated business requirements into actionable data product features.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills, especially around data quality and governance. Prepare scenarios where you had to resolve conflicting business rules or ensure compliance controls were met, and be ready to discuss the outcomes of those situations.