Data Analyst

The NRLA: Who we are

The UK’s largest membership organisation for private residential landlords, the National Residential Landlords Association (NRLA) supports and represents more than100,000 members across England and Wales.

Created by landlords, for landlords, it offers investors everything they need to run a successful and compliant lettings business, whether they are full-time property professionals running large portfolios or accidental landlords with a single let.

The NRLA is a trusted ally, on hand to guide members through the complex regulatory environment, with all the essential documents and guidance needed to run a successful and fully compliant business.

A truly member-first organisation, innovation is at the heart of what we do and have invested in and developed new proptech solutions for members, including the acquisition of property safety certification firm Safe2 and the development of property management system Portfolio.

A dynamic and fast-paced organisation, the NRLA is a great place to work, and it is not just us saying that, we have Investors in People Gold status to prove it. The association was also named one of the best companies to work for in the UK in a list compiled by The Sunday Times.

Our enthusiastic and ambitious staff work out of offices in Central Manchester and Central London with hybrid working options available. Colleagues typically work from home four days a week with one day in the office.

We are looking for colleagues who are professional, adaptable, and innovative. In return we offer an inclusive and creative working environment with attractive options for training and career development and a competitive salary and benefits package.

The NRLA package:

25 days annual leave increasing to 26 days with three years’ service, 27 days with five years’ service and 28 days with seven years’ service

Additional annual day off for your birthday

Salary exchange Pension scheme

Life assurance

Cash plan health and wellbeing benefit including Employee Assistance Programme and counselling service

Sick pay

Cycle purchase loans, season tickets loans and interest-free staff loans

Complimentary NRLA membership

Non-contractual annual performance-related bonus scheme

Enhanced maternity and paternity pay

Location:

Manchester/London – Hybrid

Key Working Relationships:

Deputy Director – Data and Insights: sets the data strategy, standards and priorities. This role delivers within them and brings forward ideas for what the function should do next. The wider Technology team: developers in the Head of Product Development’s team, who build the applications the warehouse draws data from, and the DevOps Manager’s team, who provide the infrastructure, identity and integration tooling the pipelines run on. Product owners and Business Analysts in the Product Directorate; colleagues across the NRLA as users of reporting and insight and owners of source data; consultants and suppliers working on the warehouse, personalisation and AI.

Main Purpose and Scope Of Job:

Turn the NRLA’s data into insight the business acts on, and into the clean, well-modelled data that personalisation and AI depend on. The Data Analyst works with colleagues across the business to understand, translate and scope their requirements, builds reports and analysis from the data warehouse, and works with the rest of the team to extend and enrich it.

The role supports the NRLA 2.0 ambition to give every member a personalised experience: it prepares and tests the data behind segments, models and recommendations, measures whether personalisation is working, and helps bring AI into the team’s own work and into NRLA products. It raises data literacy across the business and asks what decision each request will inform, so that the team’s work changes what the NRLA does for members.

Duties and key responsibilities

Insight and reporting:

• Create reports and dashboards fit for purpose and to a high standard in Power BI, built from centrally managed semantic models, so that colleagues have one agreed version of each measure.
• Engage with users to scope work, translate business requirements into technical specifications, and agree priorities with the Deputy Director.
• Complete ad hoc requests for data and analysis from structured and raw sources, and turn repeated requests into reports or self-service tools.
• Present findings in plain language with the limits of the data stated, say what the evidence suggests the business should do, and contribute to the regular insight report on membership growth, churn and engagement.

Data Warehouse Development:

• Take part in the continuing development of the data warehouse using ELT techniques and industry-standard methodologies, on the platform the function runs (currently Snowflake, with a move to Microsoft Fabric under evaluation), including testing that reports and models give the same results on any new platform.
• Ingest new data from sources inside and outside the business in various formats and technologies, transform it to agreed standards and models, and make it available for Power BI and for the applications and services that consume it, including documented data products and APIs.
• Ensure data quality in the output, feed issues back to the owners of source systems and track them to resolution.
• Work to production standards: pipeline and model code in version control, automated tests on transformations, monitoring of pipeline runs, and documentation another team member could work from.

Personalisation and AI:

• Prepare, join and test the data behind personalisation (member attributes, property data, activity and engagement signals) so that segments, propensity models and recommendations run on data that is complete, current and correctly joined.
• Build and maintain the reporting that shows whether personalisation is working: which members received what, how they responded, and the effect on engagement, retention and take-up of services.
• Support the development and monitoring of machine learning and AI models on NRLA data: feature preparation, evaluation against agreed measures, checks for bias and accuracy, and monitoring in production. Help curate the NRLA’s guidance and content so that AI services for members, such as the NRLA’s own member assistant, draw on accurate and current material.
• Use AI tools in the team’s own work (SQL and pipeline generation, documentation, testing and analysis) within the NRLA AI Acceptable Use Policy and the standards the Deputy Director sets.

Working with the business and across Technology:

• Train colleagues and build their confidence in using data, dashboards and self-service tools; manage expectations of requests and explain what the data can and cannot answer.
• Ask what decision each request will inform. Where the data shows that something the business believes is not borne out, or that a process or service is not working for members, say so with the evidence and suggest what to do instead.
• Keep relationships with the owners of source data in each department so that quality issues are resolved at source and new data needs are known early.
• Work with developers in the Head of Product Development’s team on the data the applications expose to the warehouse (APIs, events or extracts), on changes that affect existing feeds, and on the data NRLA products consume from it; work with the DevOps Manager’s team on the environments, access, secrets and integration tooling the pipelines need, following the platform standards they set.
• Take part in the Technology team’s shared practices (peer review, post-incident reviews involving data pipelines, the engineering community) and give the Deputy Director early notice of risks, blockers and ideas.

Working with the Business and across Technology:

• Train colleagues and build their confidence in using data, dashboards and self-service tools; manage expectations of requests and explain what the data can and cannot answer.
• Ask what decision each request will inform. Where the data shows that something the business believes is not borne out, or that a process or service is not working for members, say so with the evidence and suggest what to do instead.
• Keep relationships with the owners of source data in each department so that quality issues are resolved at source and new data needs are known early.
• Work with developers in the Head of Product Development’s team on the data the applications expose to the warehouse (APIs, events or extracts), on changes that affect existing feeds, and on the data NRLA products consume from it; work with the DevOps Manager’s team on the environments, access, secrets and integration tooling the pipelines need, following the platform standards they set.
• Take part in the Technology team’s shared practices (peer review, post-incident reviews involving data pipelines, the engineering community) and give the Deputy Director early notice of risks, blockers and ideas.

Standards, quality and governance:

• Work to and help review the function’s standards for data modelling, naming, testing, documentation and release.
• Handle personal data securely and lawfully at all times, apply data minimisation, raise any data protection concern with the Deputy Director without delay, and support information governance work including data quality monitoring and retrieval for subject access requests and disclosures.
• Keep up to date with technologies and practice in data, analytics and AI, and comply with NRLA policy and statutory requirements, including data protection, information security, equality and diversity, health and safety and the code of conduct.

Person Specification

Qualifications:

• Degree in a numerate, computing or related discipline, or equivalent experience.
• Power BI, Snowflake, Microsoft Fabric or Azure data certifications (desirable).

Skills and Abilities:

• Reads and writes SQL (any variant) with confidence to query, join and manipulate data; some programming for data, ideally in Python.
• Models data and builds reports in Power BI, visualising it in the way users can most easily consume.
• Translates business requirements into technical work, and explains technical limits to business users.
• Questions process and assumptions, looks for improvement, and puts the case for it with evidence.
• Excellent written and verbal communication and strong people skills for training and supporting users.
• Strong attention to detail and quality; manages own workload across competing requests; always conscious of security and the care needed with personal information.

Experience:

• Working in a data team and maintaining data structures dedicated to reporting; translating business requirements into technical workloads and managing users’ expectations.
• Power BI data modelling and report creation from shared semantic models.
• Building or maintaining ELT pipelines into a cloud data warehouse (Snowflake, Microsoft Fabric, Azure or similar).
• Preparing data for, or measuring the results of, personalisation, segmentation or marketing automation (desirable).
• Using data science or statistical models and evaluating their accuracy; using AI tools for analysis, code generation or documentation, or preparing data and content for AI systems and large language models (desirable).

Knowledge:

• Data warehouse development, including Kimball dimensional modelling, and ELT methodologies.
• How application data reaches a warehouse through APIs, events and extracts, and common data formats (JSON, XML, CSV).
• The basics of machine learning and AI applied to customer or member data, and the limits and risks of AI-generated output.
• UK GDPR and the handling of personal data; data governance practice and the private rented sector (desirable).

Personal Attributes and other Requirements:

• Curious about members and the business, and about what the data says.
• Candid and constructive when the evidence disagrees with what people expect.
• Collaborative with colleagues across the business and the Technology team; takes ownership of the quality of their work and keeps developing their skills.