We are seeking a skilled Data Analyst to join our team. The ideal candidate will have expertise in data analysis tools and techniques, including Power BI and Tableau. The Data Analyst will play a crucial role in interpreting data, analyzing results, and providing insights to enhance business decisions.
-A strong background in a data or analytics engineering role, underpinned by a solid command of advanced Python and SQL for data manipulation and analysis.
-Solid understanding of PySpark or similar distributed computing systems.
-A good understanding of the principles and components involved in the product ionization of machine learning models.
-Demonstrate expertise in data preparation, ensuring that data is accurate and primed for use across the business.
-Skilled in data system orchestration, with the ability to manage workflows and processes to support a robust data environment.
-Knowledgeable in ETL processes, and able to leverage your technical abilities to streamline and enhance data operations.
Entry Requirements:
· A degree in computer science or any equivalent.
· Minimum 4 years of experience as a data analyst with proficiency in SQL, Python or other relevant languages for Data Analyst.
· Experience with cloud-based data platforms is beneficial but not essential
· Prior experience working in a start-up working culture is preferred
· All required training will be provided.
Skills Requirements:
· Strong analytical and problem-solving skills with the ability to translate data into actionable insights
· Highly proficient use of Excel for data analysis
· Excellent communication skills, with the ability to present complex ideas and findings in a clear and concise manner
· Ability to work independently and collaboratively in a dynamic environment
· Collaborating with cross-functional teams to define data requirements and objectives.
· Analysing complex data sets to identify trends, patterns and insights.
· Developing and maintaining data models, dashboards, and reports to support business operations.
· Ensuring data accuracy, integrity, and security throughout all stages of the data lifecycle.
· Monitor and respond to internal data requests, providing timely and accurate information.