Reporting and Analytics Developer/Data Engineer REQ92

Key Responsibilities

• Analyze the client's data needs and document the requirements.
• Refine data collection/consumption by migrating data collection to more efficient channels.
• Plan, design and implement data engineering jobs and reporting solutions to meet the analytical needs.
• Develop test plan and scripts for system testing, support user acceptance testing.
• Build reports and dashboards according to user requirements
• Work with the client's technical teams to ensure smooth deployment and adoption of new solution.
• Ensure the smooth operations and service level of IT solutions.
• Support production issues
• Apply AI coding tools such as Copilot and Coder AI to support development, testing, and code reviews.
• Use automation to improve development efficiency. This includes build, test, and deployment activities.
• Leverage AI assistance to improve code quality. This covers refactoring, defect resolution, and documentation.
• Demonstrate willingness to adopt new AI and automation tools where relevant to work outcomes.

What we are looking for

• Good understanding and completion of projects using waterfall/Agile methodology.
• Working experience using Cloudera AI (Machine Learning), Plotly and data engineering AI tool stack
• Strong SQL, data modelling and data analysis skills are a must.
• Hands-on experience in big data engineering jobs using Python, Pyspark, Linux, and ETL tools like Informatica.
• Hands-on experience in a reporting or visualization tool like SAP BO and Tableau is must.
• Hands-on experience in DevOps deployment and data virtualisation tools like Denodo will be an advantage.
• Hand-on experience in scripting like python and shell scripts will be an advantage
• Track record in implementing systems using Hive, Impala and Cloudera Data Platform will be preferred.
• Good understanding of analytics and data warehouse implementations.
• Ability to troubleshoot complex issues ranging from system resource to application stack traces.
• Track record in implementing systems with high availability, high performance, high security hosted at various data centres or hybrid cloud environments will be an added advantage.
• Passion for automation, standardization, and best practices.
• AI and automation scope past experience will be an advantage.