Data Analytics Platform Engineer
Nairobi, Kenya
Safaricom
Discover Safaricom's mobile, data, and M-PESA services in Kenya. Seamless connectivity, innovative solutions, and exclusive offers await you!Reporting to the DataOps Engineering Lead, the position holder will play a pivotal role in designing, implementing, and maintaining a robust data analytics platform. You will work closely with data engineers, machine learning engineers, data scientists, and software engineers to ensure seamless data integration, processing, and analysis. This role requires a strong understanding of data analytics principles, software engineering best practices, and the ability to architect scalable and efficient data platforms.
- Platform Architecture: Design and develop a scalable and extensible data analytics platform to support the organization's data-driven initiatives. Architect data pipelines, storage solutions, and analytics frameworks to handle large volumes of data efficiently.
- Data visualization - Creating visualizations such as charts, graphs, and dashboards to communicate insights effectively to stakeholders.
- Data Integration and Processing: Implement data ingestion pipelines to integrate data from various sources, including databases, data warehouses, APIs, and streaming platforms. Develop ETL (Extract, Transform, Load) processes to preprocess and clean raw data for analysis.
- Analytics Tools and Technologies: Evaluate, select, and integrate analytics tools and technologies to support data exploration, visualization, and modeling. Implement and optimize databases, data warehouses, and analytics frameworks such as SQL, Hadoop, Spark, and Elasticsearch.
- Scalability and Performance: Optimize data processing pipelines and analytics workflows for scalability, performance, and efficiency. Implement parallel processing, distributed computing, and caching mechanisms to handle large-scale data analytics workloads.
- Data Governance and Security: Ensure compliance with data governance policies, regulatory requirements, and security best practices. Implement access controls, encryption, and auditing mechanisms to protect sensitive data and ensure data privacy and confidentiality.
- Monitoring and Maintenance: Develop monitoring and alerting systems to track platform performance, data quality, and system health. Proactively identify and resolve issues to minimize downtime and ensure uninterrupted data analytics operations.
- Automation and DevOps: Implement automation pipelines for infrastructure provisioning, configuration management, and deployment. Establish continuous integration and continuous deployment (CI/CD) processes to streamline platform development and operations.
- Documentation and Training: Document platform architecture, data pipelines, and analytics workflows. Provide training and support to data analysts and data scientists to ensure effective use of the data analytics platform.
- BS or MS in computer science or equivalent practical experience
- At least 2-3 years of coding experience in a non-university setting.
- Proficient understanding of distributed computing principles
- Experience in collecting, storing, processing and analyzing large volumes of data.
- Proficiency in understanding database technologies
- Excellent written and verbal communication skills
- Understanding of big data technologies: Cloudera/Hortonworks
How to Apply
If you feel that you are up to the challenge and possess the necessary qualification and experience, kindly proceed to update your candidate profile on the recruitment portal and then Click on the apply button. Remember to attach your resume.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Architecture Big Data CI/CD Computer Science Data Analytics Data governance DataOps Data pipelines Data quality Data visualization DevOps Elasticsearch Engineering ETL Hadoop Machine Learning Pipelines Privacy Security Spark SQL Streaming
Perks/benefits: Career development
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