Data Analyst

Job Description

Role Purpose:

We are seeking a detail-oriented and highly skilled Data Analyst to join our dynamic team. This role is integral to the creation of Management Information (MI) Dashboards and will drive intelligence and insights across our organisation. The ideal candidate will have extensive experience in using Power BI and Microsoft Fabric, and will thrive in a demanding, data-led environment.  They will have a solid understanding of Master Data Management & Data Science methodologies and how to apply these relevantly within the organisation.

Key Responsibilities

• Development of Management Information Dashboards: Design, develop, and maintain interactive MI Dashboards using Power BI to provide actionable insights. This includes creating data models, developing complex DAX queries, and integrating various data sources to ensure comprehensive and real-time reporting.
• Data Analysis and Reporting: Perform in-depth analysis of large datasets to identify trends, patterns, and insights that can inform business decisions. Utilise statistical techniques and advanced analytics to support strategic planning and operational improvements.
• Driving Business Intelligence: Leverage data to drive business intelligence, ensuring data-driven decision-making processes across departments. Develop and implement BI strategies, frameworks, and roadmaps to enhance data accessibility and usability within the organisation.
• Collaboration: Work closely with stakeholders to understand their needs and deliver data solutions that meet business requirements. Facilitate workshops and training sessions to improve data literacy and empower users to utilise BI tools effectively.
• Data Engineering Expertise: Utilise SQL for data engineering tasks, ensuring data is clean, accurate, and ready for analysis. Develop ETL processes to automate data extraction, transformation, and loading from various sources.
• API Integration: Work with APIs to integrate various data sources into our data systems and dashboards. Develop and maintain API connections to ensure seamless data flow and synchronisation across platforms.
• Structured Approach: Follow a fully structured approach in all data-related tasks to maintain high standards of accuracy and consistency. Implement data governance practices and adhere to industry standards and best practices.
• Continuous Improvement: Identify opportunities for process improvements and implement solutions to enhance data handling and reporting capabilities. Stay updated with the latest trends and technologies in data analysis and BI to drive innovation.

Data Quality Management

• Data Quality Assurance: Develop and implement data quality assurance processes to ensure the integrity, accuracy, and reliability of data used in analyses and reporting. Conduct regular data quality assessments and audits.
• Data Cleansing and Validation: Perform data cleansing and validation tasks to maintain high data quality. Identify and correct data anomalies and inconsistencies in datasets.
• Data Quality Metrics: Establish and monitor data quality metrics to track the performance and accuracy of data. Report on data quality issues and work with stakeholders to resolve them effectively.
• Data Quality Tools: Utilise data quality tools and software to automate data quality checks and processes. Implement data quality frameworks to ensure consistent data quality management.

Master Data Management (MDM) Expertise

• Master Data Management Implementation: Ensure that master data is accurate, consistent, and secure across the organisation. Develop and maintain policies, procedures, and standards for MDM.
• Data Quality and Governance: Establish data quality metrics and governance frameworks to ensure the integrity and reliability of master data. Conduct regular data audits and implement corrective actions as necessary.
• Integration with Business Systems: Work with IT and business teams to integrate MDM with other business systems and applications. Ensure that master data is effectively shared and utilised across different functions and departments.
• Training and Support: Provide training and support to end-users on MDM tools and practices. Develop documentation and user guides to facilitate the effective use of MDM solutions.

Data Science Methodologies

• Machine Learning and Predictive Modelling: Apply machine learning algorithms and predictive modelling techniques to extract insights and forecast trends. Experience with regression, classification, clustering, and other machine learning techniques.
• Statistical Analysis: Perform statistical analysis to interpret complex data sets and provide actionable insights. Proficiency in statistical programming languages.
• Data Visualisation: Create advanced data visualisations to communicate findings effectively.
• Big Data Technologies: Utilise Big Data technologies and platforms such as to handle and analyse large volumes of data.
• Research and Development: Conduct research to develop and refine data science methodologies and techniques. Stay abreast of the latest advancements in data science and incorporate them into practice.

Qualifications

Required Skills and Qualifications

• Educational Background: Bachelor’s degree in Data Science, Computer Science, Information Systems, or a related field.
• Experience: Experience as a Data Analyst, with a proven track record of creating impactful dashboards and reports. Experience in a fast-paced, data-driven environment is essential.
• Technical Skills: Proficiency with Power BI and Microsoft Fabric is essential. Strong experience with SQL and working with APIs is required. Familiarity with data warehousing concepts and tools such as Azure Data Factory or equivalent.
• Data Handling: Expertise in data engineering, including data cleaning, transformation, and preparation for analysis. Knowledge of data modelling, database design, and data architecture principles.
• Data Quality: Proven experience in data quality management, including data cleansing, validation, and assurance. Familiarity with data quality tools and frameworks.
• Excel Expertise: Extensive experience in utilising Excel, including advanced skills with Pivot Tables, Power Query, and other relevant Excel functionalities. Ability to automate repetitive tasks and perform complex data analysis within Excel.
• Analytical Skills: Excellent analytical and problem-solving skills, with the ability to interpret complex data and provide insights and a proficiency in statistical analysis.
• Communication: Strong communication skills to effectively present findings and recommendations to stakeholders. Experience in writing technical documentation and creating user guides.
• Attention to Detail: High attention to detail to ensure data accuracy and quality in all deliverables.
• Organisational Skills: Ability to manage multiple tasks and projects in a fast-paced environment. Strong project management skills and experience with tools such as Jira or Trello.
• Team Player: Ability to work collaboratively with cross-functional teams and adapt to changing business needs. Experience in leading or mentoring junior analysts is a plus.

• Project Management: Experience in managing data-related projects from inception to completion. Strong understanding of project management methodologies such as Agile or Scrum.

Key Attributes

• Innovative Thinking: Ability to think creatively and propose innovative solutions to data challenges.
• Customer-Focused: Strong focus on delivering value and insights to internal clients and stakeholders.
• Curiosity: A natural curiosity to explore data and uncover deeper insights.
• Resilience: Ability to handle pressure and meet tight deadlines in a demanding data-led environment.