At Sirius, we are looking for an experienced Data Modeller to help our client, which is a large integrated energy industry provider in Australia.

Role Description
This is a daily rate contract hybrid role for the next 3 to 6 months for a Data Modeller located in Melbourne, VIC, with some work from home flexibility.
The Data Modeller will be responsible for creating, implementing, and managing robust data models (conceptual, logical, and physical), ensuring data quality and rigorous governance across the client's enterprise systems.

Key Duties and Responsibilities will include:

• Model Design and Documentation: Designing and maintaining conceptual, logical, and physical data models using industry best practices (e.g., 3NF, Dimensional, Data Vault) to support transactional, operational, and analytical needs (Data Warehouses, Data Marts).
• Performance Optimization: Collaborating with Database Administrators and Engineers to optimize physical database design for performance, including indexing strategies, partitioning, and storage procedures.
• Reverse Engineering and Analysis: Conducting in-depth source system analysis and reverse engineering of existing databases to understand data structures and identify data lineage.
• Metadata and Dictionary Management: Developing and maintaining comprehensive data dictionaries, glossaries, and metadata repositories to ensure clear understanding and standardisation across the business.
• Quality and Governance: Defining and implementing data standards, naming conventions, and quality rules to uphold data integrity and governance frameworks.
• Data Segmentation and Insights: Developing quality data segmentation strategies to enable targeted customer insights, marketing automation, and business reporting.
• Stakeholder Collaboration: Working closely with business stakeholders, subject matter experts, and data engineers to understand data needs and translate complex requirements into scalable, actionable data solutions.
• ETL/ELT Involvement: Providing technical guidance to the Data Engineering team on ETL/ELT processes, ensuring the data transformation logic aligns with the approved data model design.

Qualifications

• Extensive experience in Dimensional Modeling (Star/Snowflake Schema) and Data Vault methodologies.
• Strong experience in Data Modeling and Data Segmentation across large-scale data environments.
• Proficiency in designing and optimizing relational databases using Advanced SQL (including complex joins, window functions, and stored procedures).
• Experience with Tableau or other leading BI tools (Power BI, Looker) for validating models and building foundational reports.
• Proficiency in Data Governance and Data Quality practices, including defining and tracking key data quality metrics.
• Skilled in Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) design and pipeline development.
• Excellent analytical, conceptual, and problem-solving skills, with a focus on delivering high-performance solutions.
• Strong communication and presentation abilities to clearly articulate complex data concepts to both technical and non-technical stakeholders.
• Experience with relevant data modeling tools and software (e.g., Erwin, SqlDBM, or DataGrip).
• Bachelor's degree in Computer Science, Information Technology, or a related field.

Ideal Background

• Utilities, Integrated Energy, Telco, and Retail sector experience is highly advantageous.
• Experience in Customer Insights, Customer Segmentation, and AMI (Advanced Metering Infrastructure) data would be beneficial.
• Familiarity with Cloud Data Platforms (e.g., AWS, Azure, or GCP) is a plus.

Should you wish to discuss, please contact Kevin Gonzalez, our IT Principal Consultant (Data, AI and Cyber), via DM or apply to this job advertisement.

Your interest will be treated in the strictest of confidence and our client as well as Sirius Technology are equal opportunity employers and we encourage candidates from all backgrounds to apply.