* Duration: Up to 12 months, with the option for 12-month extensions.
* Australian Citizen, eligible to work in Canberra, Sydney, Brisbane, Adelaide, Melbourne, or Hobart, with a hybrid (3 days in-office, 2 days at-home) role.
The Senior Enterprise Data Warehouse Engineer will advise, design, model, and deliver strategic data assets to data users and customers across NDIA. This includes updating data development documentation, providing technical guidance to developers, and reviewing/approving data designs and data models.
This role focuses on collaborating with key business areas, solution architecture, and other governance committees in the development and implementation of consumable datasets to address key risks and emerging trends within these areas.
Key Responsibilities
Data Delivery
* Develop data models based on existing modelling practices, data sources, and end-user requirements.
* Own the technical implementation of new data from analysis to delivery (designing and delivering data dictionaries, defining release steps, defining best practices of data modeling, and review steps).
* Provide technical leadership to project delivery teams through design reviews, advising on implementation best practices, defining and refining release processes, and technical workshops.
* Review and refine the data delivery framework to enhance integration of new sources, performance of existing data delivery, and rapid development of new subject areas.
* Establish peer review and data modeling, development, and release standards.
* Conduct knowledge transfer sessions on best practices for development, data modeling, release processes, etc.
* Facilitate continuous improvement measures in delivery principles, coding standards, documentation, and provide training sessions to the team.
* Understand, analyze, and articulate user requirements.
* Development and maintenance of SQL analytical and ETL code.
* Optimization and tuning of SQL code to ensure optimal performance.
* Development and maintenance of system documentation.
* Collaboration with data consumers, database development, testers, and IT support teams.
The Enterprise Data Warehouse Engineer must have 10+ years of experience in similar roles and is expected to have a high level of competency:
* SQL/Teradata: Demonstrated competency in developing, auditing, and reviewing code.
* SAS (preferred), SQL (essential), or Python/R/Java (preferred): Proficiency in one or more programming languages.
* DevOps: Ability to understand DevOps processes and use DevOps tools accordingly.
* Programming: High-level competency in programming, including knowledge of supplementary programming languages like Python.
* Version control: Ability to demonstrate knowledge of version controls and its appropriate uses.
* Excel: Competency with required systems, software, and programs, including SAS and Excel.
* Other: Ability to read and interpret data models and specifications.
All applications require addressing selection criteria as part of the application submission.
1. Candidates should have 3+ years of experience in similar roles.
2. Tertiary qualifications in mathematics, statistics, computer sciences, or more than 3 years of relevant work experience.
3. Experience with updating data development based on approved data models, documentation, providing technical feedback to peers, and reviewing/creating data designs and data models.
4. Experience in reviewing data modeling, development, and release standards.
Required Skills:
User Requirements, Project Delivery, Version Control, SAS, Steps, Analysis, DevOps, Programming Languages, Reviews, Continuous Improvement, Workshops, R, Auditing, Developers, Architecture, Specifications, Integration, Mathematics, Programming, Python, Documentation, Software, Java, SQL, Leadership, Maintenance, Design, Business, Training.