Senior Data Analyst

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Job Description

Responsibilities :

Data Processing and Data Quality
Source relevant data from various databases, models and stakeholders internal and external.
Ensure absolute data integrity in the collection, analysis and interpretation process.
Adhere to any relevant business rules that govern the data collected.
Ensure that relevant data are collected daily / weekly / monthly as prescribed by the SOPs
(standard operating procedures) of relevant stakeholders.
Continuously strive to implement automated methods of data collection that adhere to data
integrity standards.
Perform relevant ETL processes on large-scale data in an Azure environment.
Clean and pre-process the collected data to enhance data integrity, quality and consistency.
Aggregate data according to prescribed methods in order to meet specific business
Export and deliver data in various formats as per the objectives of the data processing
Implement best practices for data validation and quality control.
Dashboard Development and Presentation
Build interactive PowerBI dashboards tailored to specific business needs.
Synthesize current business intelligence or trend data to support recommendations for action, forecasting and/or projections.
Present data insights and findings to stakeholders in a clear and understandable manner.
Understand and propose best statistical analysis methods relevant to specific business needs.
Translate data into actionable information for informed decision-making.
Provide guidance to relevant stakeholders where needed on the solutions provided.
Provide insights that drive business value in strategic decision making.
Conduct timeously follow-up with relevant stakeholders to confirm if needs are met.
Stakeholder Collaboration and Requirements
Consult with relevant stakeholders and managers to understand the needs, goals and strategic objectives that drive the analysis requests.
Organise insights into agreed format for business, such as monthly reporting, daily tracking etc.
Work closely with business stakeholders to gather data requirements.
Collaborate with stakeholders to understand and incorporate their requirements into the dashboards.
Maintain open communication channels to address stakeholder feedback and evolving data requirements.
Maintenance, Support, and Documentation
Take responsibility for the ongoing maintenance and optimization of data solutions.
Collaborate with data engineering and other relevant teams to address technical issues, ensure system stability, and provide timely support.
Document data processes, methodologies, and best practices for team reference and knowledge sharing.
Create and maintain documentations including requirements, design and user manuals as needed.
Mentor and assist junior team members in their roles and provide guidance on best practices
where required.

Requirements :

Bachelor’s Degree in a relevant quantitative field (e.g., Data Science, Engineering, Statistics, Computer Science). NQF 7.
Additional Certifications in Azure environment would be advantageous.
A minimum of 4 years of relevant experience in data analytics, other relevant fields will be considered such as data science, data engineering, machine learning or BI development.
At least 2 years in senior data analyst role advantageous
A working knowledge and understanding of the following:
Python, DataBricks, PySpark, Azure, SQL, PowerBI, and GIS.
Experience in other similar cloud services will be considered.
Strong hands-on experience with ETL processes and data aggregation methods.
Excellent analytical and problem-solving skills, with the ability to easily determine best statistical analysis methods on large and different datasets.
Ability to translate business needs into data-driven solutions, and then to present it with the relevant business acumen to internal and external stakeholders.
Effective communication and collaboration abilities to work closely with cross-functional teams.
Detail-oriented mindset with a commitment to delivering high-quality, actionable insights.
Experience in the Telematics or automotive industry is a plus.
Technologies Experience: Working experience in a cross-section of the following technologies (recent 2 years) is required:
Project Participation: Agile frameworks like Scrum or Kanban.
Programming: Python (Pandas, Matplotlib, Seaborn, Plotly, Jupyter Notebooks, GeoPandas), Excel.
Cloud data: DataBricks (PySpark, SQL, NoSQL), PowerBI.
Geospatial: QGIS is advantageous.
Maths and Statistics: Statistical techniques and hypothesis testing.


Salary: negotiable