Wonderful oppprtunity -
Urgently seeking a Business Intelligence analyst which has ideally worked on QlikView/ Qlik Sense for our client in the Logistics and supply chain sector .
This will be an onsite role .
Requirements
- Bachelors degree in business, economics, statistics, computer science, or a related field.
- Proven experience as a business intelligence analyst, data analyst, or similar role.
- Proficiency in SQL for data extraction and manipulation.
- Experience with business intelligence and data visualization tools such as Tableau, Power BI, or Qlik.
- Strong analytical skills with the ability to analyse complex datasets and derive meaningful insights.
- Familiarity with statistical analysis techniques, data modelling, and predictive analytics.
- Excellent communication and presentation skills, with the ability to convey technical concepts to non-technical audiences.
- Attention to detail and accuracy in data analysis and reporting.
- Ability to work independently and collaboratively in a fast-paced environment.
- Knowledge of data warehousing concepts and ETL processes is desirable.
- Experience with programming languages such as Python or R for data analysis and modelling is a plus.
- Familiarity with cloud platforms such as AWS or Azure for data storage and analytics.
Responsibilties:
Data Collection and Analysis:
- Collect, clean, and analyse data from multiple sources, including databases, spreadsheets, and external systems. Use SQL queries, data mining techniques, and statistical analysis to extract insights and identify trends.
Reporting and Visualization:
- D evelop reports, dashboards, and visualizations using business intelligence tools such as Tableau, Power BI, or QlikView. Present data findings in a clear, concise, and visually appealing manner to facilitate understanding and decision-making.
Business Insights:
- Translate data into actionable insights and recommendations to support strategic and operational initiatives. Identify key performance indicators (KPIs) and metrics to measure business performance and monitor progress towards goals.
Forecasting and Predictive Modelling:
- Build predictive models and forecasting algorithms to anticipate future trends and outcomes. Use statistical techniques and machine learning algorithms to analyse historical data and make data-driven predictions.
Data Governance and Quality:
- Ensure data integrity, accuracy, and consistency by implementing data governance policies and procedures. Perform data validation, quality assurance, and data cleansing activities to maintain high-quality data standards.
Collaboration and Communication:
- Collaborate with cross-functional teams, including business stakeholders, IT professionals, and data engineers, to understand business requirements and data needs. Communicate findings, insights, and recommendations to stakeholders in a clear and compelling manner
Continuous Improvement:
- Stay informed about emerging trends, technologies, and best practices in business intelligence and data analytics. Continuously improve data analysis processes, methodologies, and tools to enhance efficiency and effectiveness
Training and Support:
- Provide training and support to end-users on business intelligence tools and techniques. Develop user guides, documentation, and training materials to empower stakeholders to utilize data effectively in decision-making
