DataDivers - Data Solutions Architect at Rmkble

Perth, Western Australia, Australia -

Full Time

Start Date

Immediate

Expiry Date

16 Aug, 26

Salary

0.0

Posted On

18 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Modelling, Database Design, Data Governance, Business Consulting, Enterprise Architecture, Big Data Technologies, Data Integration, Strategic Planning, SQL, Python, ETL, Data Warehousing

Industry

IT Services and IT Consulting

Description

DataDivers is on the hunt for a dynamic and driven Data Solutions Architect to join our growing team. About the role: A Data Architect is a senior and specialist role within the DataDivers.io business. This role possesses ICT technical expertise as well as considerable experience in one or more areas such as data analysis, data engineering, data manipulation and data visualisation. The Data Architect is responsible for contributing to the design and management of an organisation's data systems and infrastructure. Data Architects create blueprints for how data is collected, stored, organised and accessed across the organisation. Activities the Data Architect will undertake include modelling, database design, integrations and data governance. Data Architects use their skills and expertise to design and manage robust data architectures that align with organisational goals, thereby facilitating lasting sustainability for their clients through the delivery of pragmatic solution outcomes. This role works at an enterprise level, engaging with the client’s Executive and operational leads to understand the organisation’s data needs. The Data Architect assesses the quality of the organisation’s data, using the data to provide client insights and present views on how that insight can bring benefit to the client’s organisation. Key Responsibilities: Data Architecture Design: Primarily responsible for designing the overall data architecture of an organization, including data models, data integration patterns, database structures, and data governance frameworks. Evaluate and select appropriate data storage, processing, and integration solutions (e.g., databases, data lakes, lakehouses). Strategic Planning: Undertake planning and present strategic roadmaps to address future data needs, scalability requirements, and integration of new technologies. Understand and align data architecture with overall enterprise architecture frameworks and business strategies. Modelling: Design and create data models (conceptual, logical, and physical) for data warehouses, data lakes, lakehouses, and databases. Use data models to represent the data structure and relationships within systems representing business processes and functional areas with the business. Developing scripts or applications for data manipulation, integration, or analysis. Analyse and optimise business processes that rely on data for decision-making. Create and manage database schemas to ensure efficient data storage and retrieval. Applying techniques and tools to process and analyse large datasets, often leveraging big data technologies. Data Governance: Establish data standards, policies, and best practices to ensure data integrity and security. Implement data governance best practices to ensure compliance. Maintain documentation of data sources, pipelines, and architecture. Understand and implement data governance, quality, and lifecycle management processes. Ensure data security measures are in place to protect sensitive information and comply with regulations. Collaboration: Work with various stakeholders, such as data scientists, analysts and others to understand business requirements and align data architecture with organisational goals. Providing expert advice in specific technologies relevant to data management and architecture. Maintain strong and positive relationships with industry to stay informed about emerging technologies and trends in data management to ensure the organisation remains competitive. Skills (Level: High) Skills Framework for the Information Age (SFIA) https://sfia-online.org/en Expertise in data modelling and database design principles Business consulting experience Conceptual thinking Leadership and relationship management Communication and collaboration Define and implement processes to support data governance, quality, and lifecycle management Ability to design models to represent the data structure and relationships within the system Apply techniques and tools to process and analyse large datasets, often leveraging big data technologies Experience employing data security measures to protect sensitive information and comply with regulations Analyse and optimise business processes that rely on data for decision-making Align data architecture with overall enterprise architecture frameworks and business strategies Provide expert advice in specific technologies relevant to data management and architecture Tools / Languages & Methodologies Tools / Languages (Proficient) Database Management Systems (DBMS) for Regional and NoSQL databases MySQL, PostgreSQL, Oracle, Redis, Amazon DynamoDB Data Modelling Tools ER/Studio, IBM InfoSphere Data Architect, Microsoft Visio, Lucidchart ETL Tools Azure Data Factory, Microsoft Fabric, Databricks, Apache NiFi, Talend, Informatica, Microsoft SSIS, AWS Glue Data Warehousing Solutions Amazon Redshift, Google BigQuery, Snowflake, Microsoft Fabric, Databricks, Azure Synapse Analytics Big Data Technologies Apache Hadoop, Apache Spark, Apache Kafka, Cloudera Collaboration & Documentation Tools Confluence, SharePoint, GitHub Programming Languages SQL, Python, R, Java, JavaScript, Scala Methodologies (Proficient) Extensive experience with Data Warehousing methodologies (e.g., Ralph Kimball, Data Vault) Broad understanding of CI/CD practices in Azure, AWS, or GCP Experience of data quality and data governance processes to ensure data accuracy and reliability Experience: The Rmkble Data Architect has the following level of experience: At least 5 years’ experience in a similar role. At least 5 years’ experience in client delivery within a project / consultancy environment. Considerable experience in a leadership role(s) managing design and delivery of data solutions. Specific Qualifications: The Rmkble Data Architect should have the following minimum qualifications: Undergraduate university degree in Computer Science / Statistics, Mathematics, Science, Engineering or Technology. Masters level degree preferred.

Responsibilities

The Data Solutions Architect is responsible for designing and managing an organization's data systems, including blueprints for data collection, storage, and governance. They collaborate with executive leads to align data architecture with business goals and provide strategic roadmaps for scalability.