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Data Analytics Consultant (45K - 55K)
About Us:
Our client ison the cutting edge of data-driven transformation. Theirmission is to empower businesses by turning complex data into actionable insights.
They partner with organisations across various industries, leveraging the latest tools and technologies to drive growth, optimise operations, and create strategic advantages. If you are passionate about solving real-world business challenges using data, then this opportunity does just that!
The Opportunity
We are seeking a highly skilled and driven Data Analytics Consultant with expertise in ERP systems, SQL, PowerBI, Python, and R to join our client.
In this role, you will collaborate with clients to unlock the full potential of their data by designing, developing, and delivering impactful analytics solutions. Ideally you will hve experience analysing financial date and complex data sets to produce financial models and dashboards.
Your ability to bridge the gap between technical analytics and business strategy will make you an invaluable partner to clients looking to optimise their processes and make data-driven decisions.
Key Responsibilities:
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ERP System Expertise: Analyse and optimise data flows from major ERP systems (SAP, Oracle, Microsoft Dynamics, etc.) to ensure seamless integration with analytics tools. Provide actionable insights from ERP data to drive business efficiency.
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Data Modeling & Analysis: Utilise SQL, Python, and R to extract, transform, and analyse data from complex databases. Develop advanced data models that solve business challenges and identify trends, patterns, and insights.
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PowerBI Reporting: Build and maintain visually compelling and interactive PowerBI dashboards to present insights in a user-friendly manner. Enable clients to make informed decisions by visualising KPIs, metrics, and other business-critical data.
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Client Consulting: Work directly with clients to understand their business needs and translate them into tailored analytics solutions. Provide expert advice on leveraging data for operational improvement, cost reduction, and strategic planning.
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Automation & Optimisation: Develop and implement data pipelines and automation tools using Python and R to streamline repetitive data processes, reducing manual work and increasing efficiency.
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Collaboration: Partner with cross-functional teams, including IT, finance, and operations, to ensure alignment on data initiatives. Serve as a bridge between technical and non-technical stakeholders
