Designs and implements data pipelines, ETL processes, and reporting solutions to meet analytical needs using Python, PySpark, and big data tools like Cloudera. Focuses on automation, data modeling, and troubleshooting for government/authority data systems.
Key Responsibilities
Analyse the Authority'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 Authority'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.