Analytics Engineer - South Africa at Palladium: Make It Possible

 Primary Duties and Responsibilities: 

• Collaborate with stakeholders to understand their data needs and develop analytical solutions to address business challenges.
• Design, develop, and maintain scalable data models, pipelines, and architectures for efficient data extraction, transformation, and loading (ETL) processes.
• Perform data cleansing, aggregation, and validation to ensure data accuracy, completeness, and consistency.
• Analyze complex data sets using statistical techniques, data mining, and machine learning algorithms to identify patterns, trends, and insights.
• Develop and implement data visualizations, dashboards, and reports to effectively communicate analytical findings to both technical and non-technical stakeholders.
• Collaborate with data scientists and analysts to support their analytical needs and facilitate the integration of data models into production systems.
• Monitor data quality and performance of analytics solutions, identifying and resolving issues to ensure reliable and accurate outputs.
• Stay up-to-date with emerging trends, technologies, and best practices in analytics, data engineering, and data visualization.
• Contribute to the continuous improvement of data processes and infrastructure by identifying opportunities for automation, optimization, and efficiency gains.

Required Qualifications:

• Bachelor's Degree in Computer Science, Engineering, Statistics, or a related field.
• Proven work experience as an Analytics Engineer or in a similar role, with a focus on data engineering, statistical analysis, and data visualization.
• Proficient in programming languages such as Python, R, or SQL, with experience in data manipulation, analysis, and automation.
• Strong understanding of database systems, data warehousing, and ETL processes.
• Experience with data visualization tools such as Tableau, Power BI, Apache Superset, Metabase or similar.
• Solid knowledge of statistical analysis techniques and machine learning algorithms.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Hadoop, Spark) is a plus.
• Strong problem-solving skills with the ability to analyze complex datasets and derive meaningful insights.
• Excellent communication skills with the ability to effectively present analytical findings to both technical and non-technical audiences.
• Detail-oriented and highly organized with the ability to manage multiple priorities and meet deadlines in a fast-paced environment.