In this pivotal role, you will play a key role in designing, developing, and maintaining our data infrastructure, ensuring the efficient and reliable flow of data to support critical business needs. You will collaborate with data analysts, data scientists, and other stakeholders to translate business requirements into robust data solutions, ultimately driving data-driven decision making across the organization.

Job requirements:

• Design, implement and manage scalable data pipelines ensuring optimal performance using best practices and industry-standard tools and technologies.
• Manage and maintain the ELT/ETL processes.
• Develop, manage and maintain the data warehouse, its architecture, integrations, schemas, scripts and automations
• Automate data processing tasks to improve efficiency and reduce manual work.
• Develop and implement data quality checks, proactive monitoring processes and maintenance activities on the data warehouse to ensure data integrity and accuracy.
• Develop, manage and maintain the Data infrastructure which includes the test, pre-production and production environments for the data warehouse.
• Implement a secure data framework that meets business needs
• Storing of Data in a secure and efficient manner and ensuring tight controls on access to data
• Work closely with data analysts and scientists to understand data requirements and translate them into technical specifications.
• Troubleshoot data-related issues and identify root causes to ensure consistent data delivery.
• Create documentation and processes for clear communication and knowledge transfer.
• Develop and maintain the data architecture and validations as part of the enterprise architecture project to ensure backend systems to ensure compliance.
• Stay up-to-date on emerging data technologies and trends, and continuously seek opportunities to improve the organization's data infrastructure.

Qualification:

• Bachelor's degree in Statistics, Mathematics, Computer Science, Business Analytics, or a related field.

Knowledge/Experience:

• Minimum of 4 years of experience as a Data Engineer or similar role.
• Proven experience in designing, developing, and deploying data pipelines.
• Strong programming skills in Python and experience with distributed computing frameworks (e.g., Spark).
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) a plus.
• Experience with data warehousing and data modelling concepts.