Data Analyst
Role details
Job location
Tech stack
Job description
We are an ambitious, hybrid working, customer-centric Data & Analytics team, dedicated to developing a new generation of data products that unlock significant value for the social housing sector. We operate with a focused product lens, driven by curiosity and a commitment to technical excellence.
As a Data Analyst you will work to bring together, explore and make sense of disparate data sources, which combine to create compelling stories for our clients such as developing trends and next best actions.
In this role you will work across the full range of competencies (from analytical engineering and statistical analysis to visualisation and data storytelling). We're not looking for unicorns, rather an enthusiastic, proactive data analytics professional with key foundational skills and experience, alongside a commitment to learn and develop new ones in role.
Key Responsibilities
What will you be doing?
We're convinced that the data analyst role is key to a high functioning Data & Analytics team, playing a part in many aspects of our work, here are some of the principal areas are looking for this role to progress:
- Data discovery. Evaluating new data sources and how they can enhance current/support new product propositions through appropriately designed experiments.
- Data trust. Providing analytics on the reliability of existing data including productionising ongoing monitoring with benchmarks.
- Sales support. Ensuring that our sales function is equipped with the metrics they need to support their success.
- Measuring success. Researching and developing appropriate measures of product efficacy and return on investment (ROI) in collaboration with our sector experts.
- Strategic Analytics. Identifying our clients' and business' analytical needs, organising these into clear, actionable plans, and ensuring their effective execution.
- Feature generation. Working with our data science team to explore and develop new/improved data features.
- Insight Navigation. Liaising with our clients (directly or through events, conferences, webinars etc.), to help support their data driven journeys, finding the most compelling, clean and clear approach to effectively communicating their data insights story.
- Emerging technologies. Researching augmented analytics and related artificial intelligence (AI) approaches to enhance our output - helping to implement solutions where practical.
- Evolving standards. Working with the full Data & Analytics team to further enhance our systems of work.
In short there will be plenty to keep you interested, your technical and power skills developing and a real chance to drive innovation and change.
Why should you consider this role? Alongside the work opportunities as described your
development will be supported, you will be sensibly renumerated, we will provide a compelling benefits package, and we are a great bunch of folks to work with - though we would say that!
Requirements
- An honours degree with a substantial quantitative component / data analytics playing a key role.
- 2-4 years in a data analytics, data science, data insights, or analytics engineering role.
- Experience working with real-world datasets, ideally in a commercial environment.
- Exposure to cross-functional work for example, with data science, product and
commercial teams.
What technical skills are required?
- Data Wrangling & Transformation
- Strong experience shaping and preparing data across structured, semi-structured, and unstructured formats.
- Confident working with relational and non-relational data sources.
- Skilled in cleaning, joining, aggregating, and reshaping data for analysis and modelling.
- Data Pipelines & Modelling
- Hands-on experience maintaining and creating ETL/ELT pipelines.
- Solid understanding of data modelling principles (e.g., dimensional modelling, star
- schemas, entity relationships).
- Practical experience using DBT for SQL-based transformations and modular modelling.
- Familiarity with workflow orchestration and version-controlled analytics engineering
- practices.
- Exposure to cloud-based data environments.
- Programming & Querying
- Proficient in Python and core analytics libraries (pandas, NumPy, SciPy, etc.).
- Strong SQL skills.
- Comfortable using Git for version control and collaborative development.
- Analytics, Statistics & Experimentation
- Strong grounding in statistical methods: hypothesis testing, regression (linear & logistic),
- correlation analysis, time series analysis.
- Visualisation & Reporting
- Skilled in Power BI and Excel.
- Comfortable using notebooks (Jupyter) for exploratory analysis and experiment documentation.
- Ability to translate complex findings into clear, compelling visual narratives.
Desirable
- Familiarity with Scala, HiveQL for data processing tasks.
- Understanding of Linux/Shell for data and environment operations.
- Experience working with Apache Spark and MapReduce for large-scale data processing.
- Familiarity with NoSQL technologies such as Amazon DynamoDB.
- Machine Learning (ML) / predictive and prescriptive analytics experience.
- Hands-on Tableau use.
What else are we looking for?
- Ability to work effectively both as an individual (e.g., during remote deep work) and
- within a team - supportive, collaborative.
- A keen interest in data analytics - bringing to the team, new approaches, best practice developments and analytical methods from other walks of life.
- Clear written and verbal communication, including effective communication with non technical audiences.
- Business acumen, i.e., understanding the business context with a proven ability to align
- and actively support business goals and OKRs.
- A good understanding of data governance and related best practice., * Takes ownership and thrives on improving how things are done.
- Is proactive, self-motivated, and solutions focused.
- Can influence and collaborate across teams.
- Is a critical thinker and a problem solver.
- Balances delivery detail with big-picture thinking.
- Enjoys mentoring and helping others grow.
- Is curious to experiment, iterate, learn and develop.
- Is excited to help scale a values-led SaaS company making a real difference.
Benefits & conditions
Competitive salary and rewards package including: - Private Health care , 4 x salary Life cover,
25 days annual leave, increasing to 28 after 3 year's service, salary sacrifice pension scheme and much more ..
