Data Analyst

Contract type
: B2B

Duration:
at least 4 months

Location:
remote

Overview:

We are seeking an experienced Data Analyst to support enhancement of asset data quality and readiness for AI and automation pilots

This role is pivotal in delivering the building blocks for data governance, data quality, integration, and AI-readiness programme. The analyst will help design and implement high-quality data foundations that enable strategic ambitions for 2030, including data-driven decision-making, regulatory compliance, and AI innovation.

You will work closely with internal Data & Analytics, IT, and Business Assurance teams, as well as an Ignite AI delivery team (Data Architect, Principal AI Consultant, AI/ML Engineer). The work will focus on supporting the organization's data strategy around asset data and non-asset data and implementing AI solutions while embedding new governance and quality standards across the organization

Why join:

This is an opportunity to be part of a strategic transformation that will redefine how the organization manages and leverages data. You'll play a pivotal role in building the foundation for AI, analytics, and compliance excellence, directly shaping the organization's 2030 vision for smarter, data-driven housing management.

Responsibilities:

● Support the design and rollout of a data governance framework, including ownership, stewardship, and metadata management via different governance tools.

● Conduct detailed data profiling and quality assessment across core systems (housing data, repairs, improvements, building management, contractor data, leases and others).

● Collaborate with the organization's IT teams to establish data ingestion pipelines into Microsoft Fabric (covering asset, lease, warranty, and inspection data).

● Map and reconcile data between systems, ensuring alignment with housing Data Standards and regulatory requirements.

● Support AI pilots implementation by providing AI models oversight and preparing, cleaning, and validating datasets for: warranty and maintenance extraction, documentation chatbot, computer vision for construction quality control, compliance and obligation management.

● Support dashboards creation that monitor data quality KPIs, integration performance, and AI pilot outcomes (accuracy %, hours saved, risks flagged). 1

● Work closely with business stakeholders (Property, Finance, Development, Business Assurance, Customer Experience) to document processes, validate outputs, and align data initiatives with operational goals and strategic framework.

● Produce summary reports, metadata dictionaries, and data lineage documentation for governance and audit purposes.

Qualifications:

● Proven experience as a Data Analyst, ideally within housing, property management, or other regulated sectors.

● Strong knowledge of data governance principles, metadata management, and data lineage documentation.

● Hands-on experience with data profiling, cleaning, and transformation using SQL, Power BI, Excel, or Python.

● Experience with Microsoft Azure, including Fabric, Data Lake Gen2, and Purview.

● Working knowledge of AI/ML data preparation & deployment, including NLP text extraction and image-based model validation (desirable).

● Familiarity with housing data standards, and housing sector compliance frameworks.

● Strong analytical, problem-solving, and stakeholder engagement skills - able to translate technical insights into business outcomes.

Preferred Attributes:

● Self-starter comfortable working in a hybrid, cross-functional environment.

● Strong communicator capable of engaging with both technical and non-technical stakeholders.

● Detail-oriented with a proactive approach to identifying and resolving data issues.

● Passion for data-driven transformation and continuous improvement. Outcomes:

● Established data governance programme across key systems.

● Foundation for enterprise-wide data strategy successfully implemented.

● Measurable improvement in data quality, data standards, and data integration.

● AI pilots supported with clean, validated datasets and ready for scale-up.