At a Glance
- Tasks: Lead data analytics strategy and develop impactful reporting solutions.
- Company: Global engineering and manufacturing leader with a focus on innovation.
- Benefits: Competitive salary, excellent benefits, and opportunities for professional growth.
- Other info: Collaborative environment with exposure to cutting-edge technologies.
- Why this job: Shape the future of data analytics and drive performance through data-led decisions.
- Qualifications: Strong data analytics background and leadership experience required.
A global engineering and manufacturing company is looking for a Data Analytics Manager to lead its data and analytics capability. This is a leadership role with responsibility for analytics strategy, governance, reporting, and platform development, helping the business drive performance through data-led decision making.
Working closely with senior stakeholders across Finance, Commercial, Engineering, Manufacturing Operations, Product Management, and Supply Chain, you will lead a small team delivering analytics solutions, reporting platforms, and low-code technologies.
Key Responsibilities
- Develop and maintain the organisation's data and analytics strategy and governance framework.
- Partner with business leaders to translate requirements into meaningful dashboards and reporting solutions.
- Lead and develop a team of data and analytics professionals.
- Oversee data warehousing, ETL/ELT processes, master data management, and reporting capabilities.
- Deliver executive dashboards, self-service BI, operational reporting, and predictive analytics solutions.
- Manage the Data & Analytics budget and technology roadmap.
Skills & Experience
- Strong understanding of data warehousing, databases, analytics platforms, and ETL/ELT processes.
- Experience with Power BI and Microsoft reporting technologies.
- Knowledge of Microsoft Power Platform and Power Apps.
- Experience with SAP data structures, integrations, and Data Services (BODS).
- Understanding of Master Data Management and SAP Information Steward.
- Experience with Microsoft Fabric, including Lakehouse, Pipelines, Warehouse, and Semantic Models.
- Exposure to AI and advanced analytics, including predictive modelling and machine learning concepts.
- Previous experience leading teams and engaging with senior stakeholders.
If you have the skills and experience to lead and develop a modern data and analytics function, please get in touch for a confidential discussion.
Data Analytics Manager employer: M4 Partners
As a leading global engineering and manufacturing company, we pride ourselves on fostering a dynamic work culture that prioritises innovation and collaboration. Our Data Analytics Manager role offers not only a competitive salary and excellent benefits but also the opportunity to lead a talented team in a vibrant Central Belt location, where employee growth is supported through continuous learning and development initiatives. Join us to make a meaningful impact by driving data-led decision making across various business functions.
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We think this is how you could land Data Analytics Manager
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We think you need these skills to ace Data Analytics Manager
Some tips for your application 🫡
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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How to prepare for a job interview at M4 Partners
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
