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- Tasks: Gather, interpret, and visualise data to support a digital transformation in logistics.
- Company: Join an established logistics company undergoing an exciting digital transformation.
- Benefits: Enjoy hybrid work options, a supportive team culture, and clear career progression opportunities.
- Why this job: Make a tangible impact while working in a modernising environment with flexible arrangements.
- Qualifications: 1-3 years of data analytics experience; strong skills in Python, SQL, and dashboard tools.
- Other info: Experience in logistics or system migrations is a plus but not essential.
The predicted salary is between 30000 - 35000 £ per year.
Location: Coventry (Hybrid/On-site options available)
Salary: £30,000 - £35,000
Industry: Logistics & Warehousing
Intellect Group is delighted to be recruiting on behalf of an established and growing logistics (pick and pack) company, currently undergoing an exciting digital transformation. We are seeking a Data Analyst to support the transition to a bespoke Warehouse Management System (WMS).
As the company modernises its operations, the Data Analyst will play a key role in gathering, interpreting, and visualising critical business data to ensure a smooth system integration and to optimise operational performance.
Key Responsibilities:
- Work closely with operational teams and the WMS implementation team to map existing processes and data flows.
- Extract, clean, and transform large datasets to support warehouse operations.
- Develop dashboards and reports in Power BI or Tableau to monitor key metrics before and after the WMS launch.
- Write and optimise SQL queries to manipulate and analyse warehouse and inventory data.
- Build Python scripts for data processing, automation, and integration tasks.
- Provide actionable insights to warehouse and leadership teams based on data analysis.
- Assist with data migration, validation, and quality assurance processes during the system transition.
Key Requirements:
- Experience required ranges from 1-3 years of experience in data analytics.
- Strong experience with Python for data manipulation and automation.
- Proficient in SQL for querying and managing relational databases.
- Skilled in Power BI and/or Tableau for dashboard creation and reporting.
- Excellent problem-solving skills and attention to detail.
- Ability to work collaboratively with both technical and non-technical stakeholders.
- A self-starter with a proactive approach to data challenges.
Desirable (Nice to Have):
- Previous experience within the logistics, supply chain, or warehouse management sectors.
- Experience working on system migrations or WMS implementations.
- Understanding of pick and pack processes and warehouse KPIs.
Why Apply?
- Join a business at a critical and exciting stage of growth and modernisation.
- Opportunity to make a tangible impact with your work.
- Supportive team culture and flexible working arrangements.
- Clear opportunities for career progression as the business scales operations.
Data analyst / analyst employer: Intellect Group
Contact Detail:
Intellect Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data analyst / analyst
✨Tip Number 1
Familiarise yourself with the logistics and warehousing industry. Understanding the specific challenges and processes in this sector will help you demonstrate your knowledge during interviews and show how you can contribute to the company's digital transformation.
✨Tip Number 2
Brush up on your SQL skills, especially focusing on writing and optimising queries. Being able to showcase your ability to manipulate and analyse data effectively will be crucial, as this is a key requirement for the role.
✨Tip Number 3
Gain hands-on experience with Power BI or Tableau by creating sample dashboards. This practical knowledge will not only enhance your skill set but also provide you with concrete examples to discuss during your interview.
✨Tip Number 4
Network with professionals in the logistics and data analytics fields. Engaging with others in the industry can provide valuable insights and potentially lead to referrals, increasing your chances of landing the job.
We think you need these skills to ace Data analyst / analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data analytics, particularly with Python, SQL, and tools like Power BI or Tableau. Use specific examples that demonstrate your skills in data manipulation and reporting.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company's digital transformation. Mention how your background aligns with their needs, especially your experience in logistics or warehouse management if applicable.
Showcase Your Technical Skills: When detailing your experience, emphasise your proficiency in SQL and Python. Include any projects where you developed dashboards or automated processes, as these are key responsibilities for the role.
Highlight Problem-Solving Abilities: Provide examples of how you've tackled data challenges in previous roles. This could include optimising data flows or providing actionable insights that led to improved operational performance.
How to prepare for a job interview at Intellect Group
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and data visualisation tools like Power BI or Tableau. Bring examples of past projects where you successfully used these skills to solve data-related challenges.
✨Understand the Logistics Industry
Familiarise yourself with key concepts in logistics and warehouse management. Knowing about pick and pack processes and relevant KPIs will help you demonstrate your interest and understanding of the industry during the interview.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities. Think of specific instances where you faced data challenges and how you approached them, as this will showcase your analytical mindset and attention to detail.
✨Emphasise Collaboration Skills
Since the role involves working closely with both technical and non-technical teams, be ready to discuss your experience in collaborative environments. Highlight any instances where you successfully communicated complex data insights to stakeholders.
