Data Engineer

Job Specification – Data Engineer

Job Summary

We are seeking a Data Engineer to rapidly prepare, integrate, and structure data that underpins the Innovation Unit's AI experiments and proofs of concept.

This role is critical in enabling fast hypothesis testing by ensuring the Strike Team has access to high-quality, accessible, and compliant data.

Unlike a production-only data engineering role, this position focuses on:

• fast, pragmatic extraction and transformation
• early-stage experimentation
• assessing the feasibility of AI opportunities based on data readiness
• shaping minimal pipelines that support rapid PoCs
• preparing the groundwork for scalable solutions if a concept succeeds

You will work closely with Full-Stack Prototypers, Product Strategists, Data Scientists, and compliance teams to ensure data is usable, safe, and fit-for-purpose at each stage of the discovery and testing lifecycle.

This role offers the opportunity to tackle some of the most challenging data problems in the home-buying and mortgage market while influencing what LMS builds, buys, or stops.

Key Responsibilities

1) Data Readiness & Feasibility Assessment (Discovery Phase)

a) Assess whether data required for a potential AI opportunity exists, is accessible, and is of acceptable quality.

b) Perform rapid data exploration to identify gaps, constraints, and risks.

c) Advise Product Strategists and Engineers on feasibility early in the ideation process.

d) Recommend alternative data sources or lightweight workarounds to enable experimentation.

2) Rapid Data Preparation for PoCs (Test Phase)

a) Extract, clean, and transform small-to-medium datasets to support PoCs and experiments.

b) Build minimal, pragmatic pipelines that enable rapid iteration.

c) Collaborate with Full-Stack Prototypers to feed prototypes with the right data structures.

d) Prepare synthetic or anonymised datasets where required for compliance.

3) Data Integration & Interoperability

a) Integrate data from property systems, conveyancing platforms, lender LOS, HMLR, and third-party services.

b) Ensure alignment with emerging Open Property Data standards (OPDA, PDTF).

c) Design simple, well-documented data contracts for prototype-to-backend interactions.

4) Scaling Pathway & Architecture Support (Scale or Stop Phase)

a) Translate successful PoCs into scalable data designs for production teams.

b) Define what is needed to move from "prototype pipeline" to robust enterprise-grade data flows.

c) Work with Solution Architects and Engineering leads to support future technical decisions.

5) Data Quality, Governance & Responsible AI Enablement

a) Ensure data handling meets GDPR, FCA, PRA, and internal governance standards.

b) Contribute to metadata, lineage, and documentation practices from early stages.

c) Support Responsible AI teams by enabling transparent and auditable data flows.

d) Promote privacy-by-design and safe data usage in all experiments.

6) Collaboration & Cross-Unit Enablement

a) Partner with Data Scientists on model inputs and evaluation datasets.

b) Work closely with Product Strategists to shape credible, data-backed hypotheses.

c) Share learnings with the wider organisation to improve data understanding and reuse.

d) Contribute to decision-making on buy-vs-build for data-related technologies.

Key Skills and Qualifications

• Proficiency in SQL, Python, and ETL/ELT workflows.
• Strong experience with cloud data platforms (AWS, Azure, GCP).
• Ability to work with incomplete, inconsistent, or legacy data sources.
• Understanding of data governance, quality, security, and compliance.
• Experience integrating disparate systems with APIs, flat files, or event streams.
• Ability to design simple but effective data structures for prototypes.
• Strong debugging and analytical skills.
• Familiarity with OPDA/PDTF or willingness to rapidly learn emerging data standards.
• Comfortable working at pace, making pragmatic choices, and iterating quickly.

Qualifications and Experience

• 4+ years' experience in data engineering or adjacent roles.
• Experience delivering PoCs, prototypes, or early-stage data experiments desirable.
• Demonstrated ability to handle complex data environments (PropTech, BFSI, LegalTech preferred).
• Experience integrating multiple systems and datasets.
• Degree in Computer Science, Data Engineering, or equivalent experience advantageous.

Job Types: Full-time, Fixed term contract

Contract length: 6 months

Pay: £350.00-£450.00 per day

Benefits:

• Work from home

Work Location: In person