What you'll do

We're looking for someone genuinely exceptional: not broadly experienced, but specifically excellent in a way you can name and prove. This role is for a data engineer who can walk into a platform someone else built, work out what is actually wrong with it, and decide what to fix first.

You'll join a small, senior Data & Analytics team at a real estate investment firm that has built a sophisticated data platform on Snowflake, pulling together 40+ data sources. Your job is to stabilize the environment, make reporting reliable, and automate the manual work, so that people can focus on the investment and operating decisions that matter.

Your work will support three areas of the business:

• Transactions: buy/sell decisions, commercial leasing, and valuation

• Reporting and source of truth: benchmarks, fund and asset performance, and management reporting

• Day-to-day decision making: giving teams faster, better access to the information they need to run the business

You'll work directly with the client's technical and business teams, assess whether the platform is as strong as it looks, and raise the standard around you through code review, documentation, and the willingness to push back when something isn't right.

What we’re looking for

Depth in data engineering is the starting point. Beyond that we’re looking at judgment: knowing which problem to solve first in an environment with a lot of moving parts, and being able to explain that choice to people who aren’t engineers. We also pay attention to how AI shows up in the way you work.

You must bring:

• 5+ years in data engineering, with real ownership of a production platform rather than contributing to someone else’s

• Hands-on Snowflake: warehouse sizing and cost management, MERGE patterns, streams and tasks, clustering

• Experience diagnosing and fixing pipelines you didn’t write: slow queries, unexplained cost, silent data quality failures

• Experience designing, implementing, and maintaining ETL/ELT pipelines and data integration across many sources

• Strong data modeling: stating and enforcing grain, clean layering from raw through staging to marts, handling corrections and late-arriving data

• Advanced SQL, including window functions and query performance work

• Experience with a transformation framework (dbt or equivalent) and an orchestrator (Airflow, Dagster, or similar)

• A working relationship with AI that shows up in how you build, not just in the tools you’ve tried

• Comfort owning work end to end: from design through deployment and support

• A quality mindset: clean code, good documentation, thoughtful testing, and attention to data quality and lineage

• Strong English communication, async collaboration skills, and a proactive approach to problems

• The ability to understand the business behind the data, not just the ticket in front of you

Bonus points for asset management or commercial real estate experience, familiarity with systems such as Yardi, MRI, RealPage, Argus, VTS, or CoStar, building analytics-ready models for BI tools (Power BI in particular), AWS Glue or EMR alongside Snowflake, exposure to workflow automation tools (Power Automate, UiPath), and a track record of mentoring other engineers.

Why You'll Love Working Here

Real impact. You'll work on meaningful products that make a measurable difference.

An outstanding team. Talented, kind, hard working people who care about their craft and about each other. No egos. No politics.

Growth. You'll be supported in growing your craft, exploring new paths, and stepping into greater responsibility, at your own pace.

A culture of excellence. We care about doing the right thing for our clients, our team, and ourselves. No burnout. No crunch. Just high quality work, delivered sustainably.

Variety and stability. We're profitable, independent, and over two decades strong. Yet every project brings a fresh challenge. You'll never be bored here.

This Role Might Not Be for You

We want to respect your time by being clear about what this role isn't. You should skip this opportunity if:

• You prefer well defined structure. If you gravitate toward a clear hierarchy and well defined roles and swim lanes, you may find our self-managed style challenging.

• Distributed work isn't your thing. If you find async communication, design documentation, and being proactive without a manager nearby difficult, our setup won't suit you.

• Inheriting an existing environment doesn't appeal. This role starts by stabilizing and improving a platform someone else built, with a lot of moving parts. If you only want greenfield projects, you'll find it frustrating.

• Feedback doesn't excite you. We're obsessed with quality and believe in continuous improvement. That means feedback that's sometimes nitpicky. If refining work until it's excellent feels over the top, this won't be a fit.

• Change makes you uncomfortable. Priorities shift and processes evolve. If ambiguity is uncomfortable, this may feel bumpy.

However, if this sounds like fuel, we'd love to talk.

How to Apply and What to Expect in the Interview Process

1. Your work. Show us the work that reflects you at your best. We'll look at depth, the quality of your thinking, and the logic behind your choices.

2. Lateral team fit. You'll speak with our Talent team about your career direction, your motivators, and our plans ahead.

3. Work trial. You'll tackle a take-home challenge that mirrors what we actually do.

4. Engineering deep dive. A collaborative session with our engineers.

5. Project fit. An interview focused on prioritisation, collaboration across disciplines, and how you handle the messy middle.