Data Analyst

Job Title: Data Analyst

Department: IT

Reports to: Data and Insight Manager

Location: Newcastle

Type: Full Time, Hybrid

Summary:

We are seeking a detailed-oriented Data Analyst to join our team. The role holder will be responsible for collecting, processing and analysing data to provide actionable insights that support decision making across the organisation. They would work closely with business stakeholders to understand data needs, create reports and dashboards, and identify trends that drive strategic initiatives. The role requires strong analytical skills, attention to detail, and the ability to communicate complex data insights to non-technical stakeholders.

Responsibilities:

1. Retrieve and analyse data from SQL Server databases using SQL queries.


2. Extract data from key systems outside of existing pipelines when required using system specific features and tools.


3. Assist in the design, enhancement, and implementation of data collection and data quality processes.


4. Ensure the accuracy and integrity of data by performing necessary data validation and cleaning processes, making recommendations to system owners for improving data quality at source.


5. Analyse business requirements and translate them into technical specifications for data reporting and visualisation.


6. Collaborate with technical colleagues, including system administrators, developers, and external partners to deliver solutions.


7. Perform quantitative analysis to uncover anomalies, patterns, trends, and insights using statistical techniques and data mining.


8. Create and maintain compelling interactive dashboards and visual reports using Power BI to illustrate key insights and performance metrics, providing actionable insights for business stakeholders.


9. Collaborate with stakeholders to understand their data needs and tailor visualisations.


10. Ensure data visualisations adhere to best practices for design and usability.


11. Work closely with cross-functional teams to address business challenges and provide data-driven solutions.


12. Support the development of data science capability within the organisation, contributing to the design and application of clustering, risk stratification, and other machine learning techniques to enrich the data model and inform reporting.


13. Present findings, insights, and recommendations to management and other stakeholders in a clear and compelling data visualisations, reports and presentations.


14. Provide ad-hoc deep dive analysis, reporting requests and management information to business users.


15. Maintain awareness of data pipeline health and BAU reporting, escalating issues to the data engineer where appropriate.


16. Create and maintain all relevant documentation, e.g. requirements, data models, data dictionaries, reports and dashboards.


17. Provide training and support to others in IT, sharing best practices and fostering culture of continuous learning.


18. Train business users in utilising dashboards and reports effectively.


19. Plan and prioritise work to ensure on time delivery of tasks.

Skills and Experience:

• Degree in Data Science, Statistics, Mathematics, Computer Science, Economics or a related field.


• Ideally previous experience as a Data Analyst or in a similar role.


• Proficiency in SQL for data extraction and analysis.


• Strong skills in Microsoft Excel for data manipulation and reporting.


• Hands-on experience with Power BI for data visualisation and reporting is preferred, especially beneficial if this is coupled with using cloud datasources and modelling in Fabric


• Strong analytical thinking and problem-solving skills with a keen eye for detail.


• Ability to communicate complex analytical concepts to non-technical stakeholders effectively.


• Knowledge of ETL processes and data warehousing concepts is a plus.


• Familiarity with statistical analysis tools and techniques.


• Understanding of A/B testing, forecasting, and predictive modelling.


• Knowledge of programming languages such as Python or R is beneficial, especially if coupled with an understanding of data science techniques and approach.


• Understanding of data governance and compliance standards.


• Ability to work both independently and collaboratively in a dynamic environment.


• Ability to prioritise tasks and work effectively in a fast-paced environment.