Data Engineering Manager - Real Estate Analytics in London
Data Engineering Manager - Real Estate Analytics

Data Engineering Manager - Real Estate Analytics in London

London Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
PricewaterhouseCoopers

At a Glance

  • Tasks: Lead a team to design and deliver data architecture for real estate analytics.
  • Company: Join PwC, a leader in innovative workplace strategies.
  • Benefits: Flexible working, private medical cover, and volunteering days.
  • Other info: Dynamic role with opportunities for professional growth and collaboration.
  • Why this job: Shape the future of real estate with data-driven insights and innovation.
  • Qualifications: Experience in data pipelines, SQL, Python, and mentoring teams.

The predicted salary is between 60000 - 80000 £ per year.

PwC’s Real Estate is a key asset to the Firm. Inspiring environments that bring our people to work together. It is critical we provide the right space for the needs of our people and the business. The Real Estate Analytics team plays a crucial role in shaping PwC’s workplace strategy by delivering data-driven insights to senior stakeholders across the firm. This includes influencing decisions on office design and future real estate investments.

This role leads the design and delivery of the team’s data architecture and engineering capability. In collaboration with your team, you will be responsible for ingesting, structuring, and managing complex datasets from multiple sources, creating scalable and well-governed data models that underpin a suite of analytics products and dashboards used across the business.

Operating within a broader enterprise data ecosystem, the team focuses on transforming and modelling data from curated sources into high-quality, analytics-ready outputs (medallion architecture), while also supporting selective ingestion of new and complex datasets where required. Alongside hands-on development, you will lead a small team, shape data strategy, and drive innovation in how data is sourced, modelled, and utilised.

What your days will look like:

  • Programme and team leadership: Oversee a programme of work, managing delivery through a high‑performing team, allocating tasks, planning workloads, mentoring individuals, and supporting ongoing professional development.
  • Data engineering and modelling: Design, build, and optimise robust data pipelines integrating multiple data sources, while developing scalable data models that transform curated data into analytics‑ready datasets.
  • Governance, performance and platform improvement: Own end‑to‑end data flow from ingestion to consumption, ensuring performance, reliability, maintainability, and strong data governance, including documentation, quality checks, and standards.
  • Stakeholder engagement and strategy: Work closely with business stakeholders, visualisation teams, and external providers to translate analytical needs into solutions, communicate insights clearly, and contribute to the broader data strategy.

This role is for you if:

  • You have hands‑on experience owning end‑to‑end data pipelines and data models, including integrating APIs and complex multi‑source datasets.
  • You bring technical skills in SQL and Python, with practical experience using platforms such as Azure Databricks, Apache Spark, and data lake or lakehouse architectures.
  • You are comfortable designing dimensional and semantic data models, transforming curated data into analytics‑ready datasets within layered architectures.
  • You value data governance and quality, with experience implementing documentation, standards, and data quality frameworks at scale.
  • You enjoy translating business problems into clear, scalable data solutions and communicating insights to non‑technical stakeholders.
  • You have experience mentoring others, collaborating across enterprise environments, and driving innovation in areas such as AI and advanced analytics.

What you’ll receive from us:

No matter where you may be in your career or personal life, our benefits are designed to add value and support, recognising and rewarding you fairly for your contributions. We offer a range of benefits including empowered flexibility and a working week split between office, home and client site; private medical cover and 24/7 access to a qualified virtual GP; six volunteering days a year and much more.

Data Engineering Manager - Real Estate Analytics in London employer: PricewaterhouseCoopers

PwC is an exceptional employer that prioritises the well-being and professional growth of its employees, particularly in the dynamic field of Real Estate Analytics. With a strong emphasis on collaboration and innovation, the company offers flexible working arrangements, comprehensive benefits including private medical cover, and opportunities for continuous learning and development. Working at PwC not only allows you to lead impactful data initiatives but also to contribute to shaping the future of workplace strategy in a supportive and inspiring environment.
PricewaterhouseCoopers

Contact Detail:

PricewaterhouseCoopers Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Engineering Manager - Real Estate Analytics in London

✨Tip Number 1

Network like a pro! Reach out to your connections in the data engineering field, especially those who work at PwC or similar firms. A friendly chat can lead to insider info about job openings and even referrals.

✨Tip Number 2

Show off your skills! Prepare a portfolio showcasing your best data projects, especially those involving SQL, Python, and data modelling. This will help you stand out during interviews and demonstrate your hands-on experience.

✨Tip Number 3

Practice makes perfect! Get ready for technical interviews by brushing up on your data pipeline knowledge and governance practices. Mock interviews with friends or mentors can help you feel more confident.

✨Tip Number 4

Apply through our website! We love seeing candidates who take the initiative. Make sure to tailor your application to highlight your experience with complex datasets and stakeholder engagement, as these are key for the role.

We think you need these skills to ace Data Engineering Manager - Real Estate Analytics in London

Data Engineering
Data Modelling
SQL
Python
Azure Databricks
Apache Spark
Data Governance
Data Quality Frameworks
API Integration
Analytics-Ready Datasets
Stakeholder Engagement
Mentoring
Data Pipeline Management
Medallion Architecture
Advanced Analytics

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Data Engineering Manager role. Highlight your hands-on experience with data pipelines, SQL, and Python, as well as any leadership roles you've held.

Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about real estate analytics and how your background makes you a perfect fit. Be sure to mention specific projects or achievements that showcase your expertise in data governance and modelling.

Showcase Your Team Leadership Skills: Since this role involves leading a high-performing team, share examples of how you've mentored others and managed projects. We want to see your ability to inspire and guide a team towards success.

Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!

How to prepare for a job interview at PricewaterhouseCoopers

✨Know Your Data Inside Out

Make sure you’re well-versed in the data engineering concepts relevant to the role. Brush up on your SQL and Python skills, and be ready to discuss how you've built and optimised data pipelines in the past. Having specific examples of your work with Azure Databricks or Apache Spark will really impress.

✨Showcase Your Leadership Skills

As a Data Engineering Manager, you'll need to demonstrate your ability to lead a team effectively. Prepare to talk about your experience in mentoring others, managing workloads, and driving innovation. Think of specific instances where you’ve successfully led a project or improved team performance.

✨Engage with Stakeholders

This role involves a lot of interaction with business stakeholders. Be prepared to discuss how you’ve translated complex data insights into actionable strategies for non-technical audiences. Highlight any experiences where you’ve collaborated with visualisation teams or external providers to deliver impactful results.

✨Emphasise Data Governance and Quality

Data governance is key in this role, so come ready to discuss your approach to maintaining data quality and implementing standards. Share examples of how you've ensured strong documentation and quality checks in your previous projects, as this will show your commitment to delivering high-quality data solutions.

Data Engineering Manager - Real Estate Analytics in London
PricewaterhouseCoopers
Location: London

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