May 26, 2026 

  May 26, 2026 

  May 26, 2026 

  May 26, 2026 

  May 26, 2026 

Design, develop, and maintain scalable data pipelines and data integration processes for collecting, transforming, and analyzing large volumes of structured and unstructured data. Analyze enterprise data sets using statistical techniques and data modelling methods to support business intelligence, predictive analytics, and data-driven decision making. Develop and implement machine learning and data processing solutions using Python and related libraries such as pandas, numpy, and scikit-learn. Build and optimize relational and NoSQL databases, including PostgreSQL, MySQL, MongoDB, and DynamoDB, to support analytical and reporting requirements. Perform data mining, cleansing, validation, and transformation activities to ensure data quality, consistency, and integrity across enterprise systems. Develop predictive models, trend analysis, and analytical algorithms to identify business patterns, operational insights, and performance improvement opportunities. Integrate and process real-time and batch data streams using technologies such as Apache Kafka, RabbitMQ, and AWS SQS to support analytics and reporting initiatives. Deploy and maintain data analytics and machine learning applications in AWS and Azure cloud environments. Create dashboards, reports, and data visualizations to communicate analytical findings and business insights to stakeholders and management teams. Collaborate with cross-functional teams to identify business problems, define analytical requirements, and deliver scalable data-driven solutions. Conduct database performance analysis, query optimization, and data modelling to improve reporting efficiency and analytics performance. Implement data governance, security standards, and access controls to ensure compliance with enterprise policies and regulatory requirements. Automate data workflows, model deployment, and reporting processes using scripting, CI/CD tools, and cloud-based technologies. ·Research and evaluate emerging data science, machine learning, and analytics technologies to enhance enterprise data capabilities. Support the development and maintenance of enterprise analytics platforms and data-driven applications to improve operational and business performance.

Job Overview

Design, develop, and maintain scalable data pipelines and data integration processes for collecting, transforming, and analyzing large volumes of structured and unstructured data. Analyze enterprise data sets using statistical techniques and data modelling methods to support business intelligence, predictive analytics, and data-driven decision making. Develop and implement machine learning and data processing solutions using Python and related libraries such as pandas, numpy, and scikit-learn. Build and optimize relational and NoSQL databases, including PostgreSQL, MySQL, MongoDB, and DynamoDB, to support analytical and reporting requirements. Perform data mining, cleansing, validation, and transformation activities to ensure data quality, consistency, and integrity across enterprise systems. Develop predictive models, trend analysis, and analytical algorithms to identify business patterns, operational insights, and performance improvement opportunities. Integrate and process real-time and batch data streams using technologies such as Apache Kafka, RabbitMQ, and AWS SQS to support analytics and reporting initiatives. Deploy and maintain data analytics and machine learning applications in AWS and Azure cloud environments. Create dashboards, reports, and data visualizations to communicate analytical findings and business insights to stakeholders and management teams. Collaborate with cross-functional teams to identify business problems, define analytical requirements, and deliver scalable data-driven solutions. Conduct database performance analysis, query optimization, and data modelling to improve reporting efficiency and analytics performance. Implement data governance, security standards, and access controls to ensure compliance with enterprise policies and regulatory requirements. Automate data workflows, model deployment, and reporting processes using scripting, CI/CD tools, and cloud-based technologies. ·Research and evaluate emerging data science, machine learning, and analytics technologies to enhance enterprise data capabilities. Support the development and maintenance of enterprise analytics platforms and data-driven applications to improve operational and business performance. $89,500.00 /year

Education and Experience Requirements

Bachelor’s degree in Computer Science or related with 3 years of experience.