At a Glance
- Tasks: Lead the development of innovative data products and ensure they meet business needs.
- Company: Join Greystar, a global leader in real estate with a focus on equality and diversity.
- Benefits: Enjoy competitive pension, healthcare, holiday allowance, and more.
- Other info: Dynamic work environment with opportunities for growth and collaboration.
- Why this job: Make a real impact by transforming data into actionable insights for the business.
- Qualifications: 5+ years in data roles, strong SQL and Python skills, and Agile experience.
The predicted salary is between 36000 - 60000 £ 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.
Stakeholder Alignment & Road Mapping
- 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.
Data Quality & Governance Enforcement
- 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.
Prototyping & Validation
- 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 at https://jobs.greystar.com/.
Data Product Lead/Engineer employer: Greystar (International)
Greystar is an exceptional employer, offering a dynamic work environment where legal professionals can thrive in the fast-paced real estate sector across Europe. With a strong commitment to employee growth, competitive benefits including healthcare and pension plans, and a culture that values diversity and equality, Greystar provides a supportive platform for legal counsel to make a meaningful impact while collaborating with talented teams on innovative projects.
StudySmarter Expert Advice🤫
We think this is how you could land Data Product Lead/Engineer
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Data Product Lead/Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Greystar (International), your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Greystar (International). Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Greystar (International)
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Greystar (International)!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
