Data Engineer [GRIT@Gov]

The GRaduate Industry Traineeship Programme within the Public Service (GRIT@Gov) aims to provide fresh graduates with opportunities to gain industry-relevant skills and experience that can strengthen their employability to take up full time roles in the sector. The Legal Operations Group (LOG) at the Attorney-General's Chambers is seeking trainees who are passionate about data engineering. This traineeship offers opportunity to develop competencies in data modelling, cataloguing, and governance for data warehousing within the legal ecosystem. Trainees will gain expertise in building and maintaining Extract, Transform, Load (ETL) pipelines on web services and implement DevOps practices in a data environment.

As a Data Engineer Trainee, you will: • Support the development and implementation of data models for our data warehouse to ensure efficiency and scalability • Assist in establishing and maintaining data cataloguing systems to improve data discovery and understanding • Build, test, and deploy ETL pipelines using AWS services, primarily Simple Storage Service (S3), Glue, and Redshift • Ensure data quality and consistency across various data sources • Develop and maintain documentation for data models, ETL processes, and data lineage • Gain exposure to working with cross-functional teams to understand data requirements and translate them into efficient data structures • Gain exposure to data governance principles and assist with enforcing data governance policies and procedures

• Bachelor's degree in quantitative disciplines such as Information Technology, Computer Science, or related fields • Strong knowledge of data modelling techniques, data warehousing concepts, and data cataloguing tools and methodologies • Proficiency in programming languages such as Python or SQL through coursework or personal projects (candidates should submit their portfolios and may be asked to complete a basic assessment in the absence of any portfolios) • Interest in legal industry processes is advantageous but not essential • Familiarity with big data technologies such as Apache Spark (PySpark), open-table storage (Delta Lake or equivalent), and AWS (Glue, Redshift) is advantageous but not essential • Excellent communication skills, both written and spoken • Ability to work independently and collaboratively as part of a team • Strong interpersonal skills and willingness to engage with various stakeholders • Eagerness to learn and develop expertise in data engineering and governance