At a Glance
- Tasks: Create interactive Power BI dashboards and analyse workforce trends for HR insights.
- Company: Join a forward-thinking HR team focused on data-driven decision-making.
- Benefits: Enjoy competitive pay, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with chances to support various HR initiatives.
- Why this job: Make a real impact by transforming HR data into actionable insights.
- Qualifications: Experience in HR analytics and strong Power BI skills required.
The predicted salary is between 35000 - 45000 £ per year.
HR Reporting & Analytics
- Design, develop, and maintain interactive Power BI dashboards to enable a self-service approach to HR data across management and leadership teams.
- Analyse workforce trends and metrics, providing actionable insights to HR leaders and key business stakeholders.
- Support workforce planning and strategic decision-making through detailed people analytics and data interpretation.
- Identify opportunities to streamline and automate recurring HR reporting processes.
Data Management & Governance
- Maintain and manage accurate employee data across HRIS and payroll systems.
- Validate, cleanse, and reconcile HR datasets to ensure reporting accuracy and reliability.
- Ensure consistency, integrity, and quality of data across multiple systems and platforms.
- Support the secure and GDPR-compliant handling of sensitive employee information.
Stakeholder Engagement & Support
- Partner with HR teams and departmental managers to understand reporting requirements and business needs.
- Present data insights and findings in a clear, concise, and non-technical manner.
- Provide ad hoc reporting, analysis, and support for business initiatives and projects.
- Assist with annual reporting activities, audits, and compliance requirements.
- Assist the wider HR team from time to time with employee lifecycle activities e.g. recruitment and employee relations support.
Skills & Experience
- Previous experience in an HR Analyst, Data Analyst, or People Analytics role, with significant exposure to sensitive people-related data.
- Strong hands-on experience developing solutions within Microsoft Power BI.
- Advanced knowledge of DAX for data analysis and reporting.
- Strong experience using Power Query for data transformation and preparation.
- Proven ability to design and build semantic data models from the ground up, including defining optimal data structures and relationships.
- Experience integrating and consolidating data from multiple systems, using different connectors, into a unified reporting model.
- Excellent analytical, problem-solving, and critical-thinking skills.
- High level of accuracy and attention to detail.
- Good understanding of GDPR principles and confidential data handling practices.
- Ability to translate business questions into meaningful data stories and actionable insights.
HR Data Analyst (Power BI) in Leicester employer: Miller Druck International Stone Ltd
As an HR Data Analyst at our company, you will thrive in a dynamic and supportive work culture that prioritises employee growth and development. We offer comprehensive training opportunities, a collaborative environment, and the chance to make a significant impact through your analytical skills in a role that directly influences strategic decision-making. Located in a vibrant area, our office provides a stimulating atmosphere where innovation and teamwork are at the forefront, making us an excellent employer for those seeking meaningful and rewarding employment.
Contact Details:
Miller Druck International Stone Ltd Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land HR Data Analyst (Power BI) in Leicester
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We think you need these skills to ace HR Data Analyst (Power BI) in Leicester
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Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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