Requirements**Academic and Professional Qualifications**** ▪       Bachelor’s Degree in Computer Science, Data Science, Information Technology, Engineering, or a related field.

▪       Professional Data Engineer Certification is a plus.

▪Optional: Master’s Degree in Data Science, Computer Science, Information Systems, or a related discipline. Experience**

▪       Extensive knowledge of data warehousing concepts, including dimensional modelling and data marts.

▪       Minimum of 5 years in data engineering, data architecture, or a related field.

▪       Experience in leading data projects or teams is highly desirable.

▪       Advanced proficiency in SQL and NoSQL with hands-on experience creating complex queries and data transformations.

▪       Proven experience with cloud-based data engineering tools such as Cloud Storage, Data flow, Cloud Composer, Cloud Functions, and AWS Glue.

▪       Set up, manage, and maintain the company’s data analytics systems, including the operational data store, feature store, and data warehouse, to support informed decision-making.

▪       Create and manage processes (ETL/ELT) for collecting, cleaning, and transforming data from different sources.

▪       Build and improve data structures to support reporting, advanced analytics, and machine learning projects.

▪       Ensure data queries run efficiently while keeping costs low and making the best use of resources.

▪       Work closely with technology and data analytics teams to develop customized data solutions and include machine learning insights.

▪       Set up and manage machine learning workflows to make sure models run smoothly and reliably.

▪       Implement data quality checks, follow governance rules, and enforce security to protect and control access to data.

▪       Automate tasks and improve processes using tools to ensure stable and scalable data pipelines.

Clearly document all processes and share knowledge to help the team adopt best practices.