Data Engineering Manager - Real Estate Analytics

PwC’s Real Estate is a key asset to the Firm. Inspiring environments that bring our people to work together. It is for this reason 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.