Total 303 data entry job vacancies in Information Technology category in sydney

2x Positions Available: We are looking for a Mid-level Data Engineer & Associate Data Engineer to join our Data Team to support the performance, integrity, and security of the organization's databases.

What is this role about?

The data engineer is responsible for building a data platform to help develop self-serve BI capability and enforce the data management practices are implemented as part of solution design. Help foster a culture of continuous improvement in processes, operations, and support by enforcing best practices and ensuring that the team consistently maximizes the efficiency and effectiveness of the platforms.

Here's more of what you’ll work on:

• Develop and Maintain AWS Data platform infrastructure code through Terraform.
• Produce the platform for extraction, loading and transformation (ELT) of data from a wide variety of data sources using ‘Big Data’ technologies by building an Integration Hub.
• Implement, review, and manage governance policies to help implement them on the data platforms.
• Manage the release of configuration changes to production environments in accordance with Cuscal change management principles.
• Manage and process complex, large data for analysis (e.g., hierarchies of datasets, inter-relationships, partitions, views, etc.)

We are responsible for collecting hundreds of millions of events from client devices each day and streaming them directly into our data warehouse. We extract data from the majority of Nine’s enterprise systems, centralise it in our data warehouse. You will be responsible for the design and overseeing the development of rich data models for analysis and to inform business operations and strategy for reporting, personalisation and commercialisation. You will play a key role in shaping and maturing the Nine data platform to enable critical business decisions and outcomes.

Who are you? 
Experienced and detail oriented data modeller to join the Nine Data team. You possess a deep understanding of data modelling techniques and best practices. You have the ability to translate complex business requirements into efficient and scalable data models.
You contribute to a learning-oriented workplace culture, being curious about the world around you, seeking new ways to explore and bring new thinking and practices to bear within your team. You remain open to learning new technologies and techniques, and finding creative ways to leverage this knowledge to further team goals.

What you’ll do:

• Design and maintain advanced data models, including conceptual, logical, physical, and dimensional modelling.
• Collaborate with broader teams to translate business needs into effective data solutions.
• Perform data profiling/analysis activities that will help establish, modify, and maintain a data model.
• Lead the creation of a taxonomy/data dictionary to communicate data requirements that are important to business stakeholders.
• Lead and participate in design workshops to facilitate an understanding of business data needs and how they are mapped to the data model.
• Support review, sign-off and adoption of data models in collaboration with data product, architecture, and data engineering teams.
• Articulating modelling principles to the broader data engineering team

Our data team has expertise across engineering, analysis, architecture, modeling, machine learning, artificial intelligence, and data science. This discipline is responsible for transforming raw data into actionable insights, building robust data infrastructures, and enabling data-driven decision-making and innovation through advanced analytics and predictive modeling. 

Responsibilities:

• Work closely with the Data Analyst/Data Scientist to understand evolving needs and define the data processing flow or interactive reports.
• Discuss with the stakeholders from other teams to better understand how data flows are used within the existing environment.
• Propose solutions for the cloud-based architecture and deployment flow.
• Design and build processes, data transformation, and metadata to meet business requirements and platform needs.
• Design and propose solutions for the Relational and Dimensional Model based on platform capabilities.
• Develop, maintain, test, and evaluate big data solutions.
• Focus on production status and data quality of the data environment.
• Pioneer initiatives around data quality, integrity, and security.

We are looking for a Lead Data Engineer to join our Data Domain!

What is this role about?

In this newly created, critical role, you will be responsible for the design, development and support of the Data Products Cuscal creates for both internal and client facing use cases. The role accomplishes this by:

• Sourcing, transforming, securing and monitoring data for the creation of products using Cuscal’s data lake and analytics systems.
• Engaging in discovery activities with the Data Product Owner and product, engineering and analytics personnel from both internal and client teams.
• Working in partnership with our Data Practice to deliver solutions that meet our organisational standards and best practices.

Here's more of what you’ll work on:

• Design Solutions: Develop and maintain scalable pipelines. Ensure systems are designed for extensibility, are robust, and can handle large volumes of data efficiently.
• Data Integration: Lead efforts in integrating data from various sources, ensuring data quality and consistency. Work on data transformation, processing, and loading to support analytics and business intelligence needs.
• Performance Optimisation: Identify and resolve performance bottlenecks within the Databricks environment, including optimizing the data ingestion processes and ensuring efficient data querying.
• Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet those needs. Provide guidance and mentorship to junior data engineers.
• Innovation and Improvement: Continuously explore new data technologies and methodologies. Implement best practices for data engineering in partnership with our Data practice.
• Documentation: Maintain comprehensive documentation of data workflows, architectures, and best practices. Ensure that all data processes are well-documented and reproducible.
• Security and Compliance: Ensure data security and compliance with industry standards and regulations. Implement data governance practices and monitor adherence to policies.

As a Data Scientist - Classifications Model Specialist at Shift, you will play a pivotal role in maintaining and evolving our classification models. You’ll be responsible for ensuring their continued success through performance monitoring, updates, and collaboration across teams. Your work will directly impact how we leverage data to drive business decisions and optimise our systems.

What you’ll do: 

• Maintain and enhance the performance of classification models through regular updates and monitoring.
• Support updates to model architecture, training sets, and model validation.
• Build and implement monitoring capabilities to effectively track model health.
• Develop and document processes to ensure smooth and consistent operations.
• Collaborate with data science, engineering, and operational teams to align on classification needs and improvements.   

Key Responsibilities:

• Design and implement the enterprise-wide data architecture strategy, including hands-on development of proof-of-concepts for new technologies and frameworks
• Architect and actively develop complex distributed systems that can scale across multiple regions and handle diverse data workloads
•  Develop, manage, and optimize ETL processes using Azure Data Factory to ensure accurate data integration across global databases
• Design, build, and maintain Microsoft SQL Server databases, ensuring data is well-organized, accessible, and secure
• Lead by example through hands-on development and implementation of advanced data processing frameworks that can be reused across multiple teams
• Define technical standards and best practices for data engineering across the organization through practical implementation and documentation
• Evaluate emerging technologies through proof-of-concept development and make recommendations for adoption or retirement of data technologies
• Identify and implement performance optimization strategies for ETL processes and reports to ensure optimal user experience
• Monitor and troubleshoot complex data processes to ensure uninterrupted service to global teams, including working occasionally outside regular business hours to support multiple time zones
• Create and maintain comprehensive technical documentation, architectural diagrams, and best practices
• Ensure data governance and compliance principles are maintained across all architectural decisions
• Communicate technical information to non-technical stakeholders effectively, tailoring the messaging as needed for diverse audiences
• Mentor and guide team members in technical best practices and architectural principles
• Collaborate effectively with cross-functional teams, including data scientists, analysts, and business stakeholders

Required Technical Skills:

• Expert-level proficiency in SQL and database optimization techniques
• Hands-on expertise in Azure services, particularly Azure Data Factory, Azure SQL Database, and Azure Analysis Services
• Deep practical experience with Data Warehousing using Kimball and STAR schema
• Strong coding abilities in at least one programming language (Python, Java, or C#)
• Hands-on experience with distributed computing frameworks
• Practical experience implementing data streaming solutions
• Expert knowledge of performance tuning and optimization techniques