Why SoftwareOne? Discover the heartbeat of SoftwareOne! Our 7 core values aren't just words – they're the beating heart of our company culture. Join us in a journey that unveils the essence of how we work, connect, and succeed. Watch the video to dive deep into the values shaping our everyday interactions, customer relations, and team spirit. Please note that SoftwareOne does not accept unsolicited resumes from recruiters or employment agencies. In the absence of a signed Services Agreement (Job-Specific per our global standard) with the agency/recruiter, SoftwareOne will not consider or agree to payment of any referral compensation or recruiter fee. The role Location: Open to either Sydney, Melbourne, Brisbane or Perth (where we have offices - Hybrid workstyle: twice-a-week work at office) We are seeking a highly skilled and experienced Solution Architect – Data Analytics for AWS to join our team and play a crucial role in designing and implementing data analytics solutions on the Amazon Web Services (AWS) platform. The ideal candidate will have a deep understanding of data analytics technologies, AWS services, and a track record of architecting scalable and efficient data solutions to address complex business challenges. Responsibilities: Report to practice lead. Work closely with sales team to develop opportunities and solution proposal. Work within project team to develop and test data analytics platform and model. Design, develop, and unit test in accordance with established standards. Assist project team in analyzing and resolving technical issues. Assist in preparing manuals, specification and other technical documentations. Package and support deployment releases. Assisting in the collection and documentation of user's requirements, development of user stories, and estimates.   Solution Design: Collaborate with cross-functional teams to gather requirements, design end-to-end data analytics solutions, and create architectural diagrams and documentation. AWS Expertise: Leverage your extensive knowledge of AWS services such as Amazon Redshift, Amazon EMR, Amazon Kinesis, AWS Glue, and others to architect robust data analytics platforms. Data Modeling: Design and optimize data models to support reporting, analytics, and business intelligence needs while ensuring data integrity and performance. Scalability and Performance: Architect solutions that are scalable, high-performing, and cost-efficient, considering factors like data volume, query complexity, and user concurrency. Data Integration: Define data 4月integration strategies to extract, transform, and load (ETL) data from various sources into the analytics platform, ensuring data consistency and quality. Security and Compliance: Implement security measures and best practices to protect sensitive data and ensure compliance with industry standards and regulations. Troubleshooting and Optimization: Identify and resolve performance bottlenecks, data quality issues, and other challenges that may arise during implementation and operation. Collaboration: Work closely with data engineers, data scientists, business analysts, and stakeholders to understand their needs and provide technical guidance. Innovation: Stay up-to-date with industry trends and emerging technologies to recommend innovative solutions that enhance our data analytics capabilities. What we need to see from you Existing full-time work rights in Australia Skills Proven experience (3+ years) as a Solution Architect /Pre-sales or similar role in Australia, with a focus on data analytics and AWS cloud technologies, and experience and knowledge on Microsoft Azure Data Analytics technology is a plus. Extensive hands-on experience with AWS services such as Amazon Redshift, Amazon EMR, Amazon Kinesis, AWS Glue, etc. Strong understanding of data modeling, ETL processes, data warehousing, and data governance principles. Familiarity with programming/scripting languages like Python, SQL, and experience with data manipulation and transformation. Excellent problem-solving skills with the ability to design and implement creative solutions for complex data challenges. Strong communication skills to effectively collaborate with technical and non-technical teams. AWS certifications (e.g., AWS Certified Solutions Architect - Associate/Professional, AWS Certified Data Analytics - Specialty) are a plus. Experience in working with Agile methodologies and version control systems. Proven ability to work independently and manage multiple priorities effectively. Education and Certification Bachelors or associate degree in IT discipline Certification in AWS Certified: Solution Architect and AWS Certified: Data Analytics Specialty are must. Job Function Software & Cloud Services

Existing full-time work rights in Australia Skills Proven experience (3+ years) as a Solution Architect /Pre-sales or similar role in Australia, with a focus on data analytics and AWS cloud technologies, and experience and knowledge on Microsoft Azure Data Analytics technology is a plus. Extensive hands-on experience with AWS services such as Amazon Redshift, Amazon EMR, Amazon Kinesis, AWS Glue, etc. Strong understanding of data modeling, ETL processes, data warehousing, and data governance principles. Familiarity with programming/scripting languages like Python, SQL, and experience with data manipulation and transformation. Excellent problem-solving skills with the ability to design and implement creative solutions for complex data challenges. Strong communication skills to effectively collaborate with technical and non-technical teams. AWS certifications (e.g., AWS Certified Solutions Architect - Associate/Professional, AWS Certified Data Analytics - Specialty) are a plus. Experience in working with Agile methodologies and version control systems. Proven ability to work independently and manage multiple priorities effectively. Education and Certification Bachelors or associate degree in IT discipline Certification in AWS Certified: Solution Architect and AWS Certified: Data Analytics Specialty are must.

Location: Open to either Sydney, Melbourne, Brisbane or Perth (where we have offices - Hybrid workstyle: twice-a-week work at office) We are seeking a highly skilled and experienced Solution Architect – Data Analytics for AWS to join our team and play a crucial role in designing and implementing data analytics solutions on the Amazon Web Services (AWS) platform. The ideal candidate will have a deep understanding of data analytics technologies, AWS services, and a track record of architecting scalable and efficient data solutions to address complex business challenges. Responsibilities: Report to practice lead. Work closely with sales team to develop opportunities and solution proposal. Work within project team to develop and test data analytics platform and model. Design, develop, and unit test in accordance with established standards. Assist project team in analyzing and resolving technical issues. Assist in preparing manuals, specification and other technical documentations. Package and support deployment releases. Assisting in the collection and documentation of user's requirements, development of user stories, and estimates.   Solution Design: Collaborate with cross-functional teams to gather requirements, design end-to-end data analytics solutions, and create architectural diagrams and documentation. AWS Expertise: Leverage your extensive knowledge of AWS services such as Amazon Redshift, Amazon EMR, Amazon Kinesis, AWS Glue, and others to architect robust data analytics platforms. Data Modeling: Design and optimize data models to support reporting, analytics, and business intelligence needs while ensuring data integrity and performance. Scalability and Performance: Architect solutions that are scalable, high-performing, and cost-efficient, considering factors like data volume, query complexity, and user concurrency. Data Integration: Define data 4月integration strategies to extract, transform, and load (ETL) data from various sources into the analytics platform, ensuring data consistency and quality. Security and Compliance: Implement security measures and best practices to protect sensitive data and ensure compliance with industry standards and regulations. Troubleshooting and Optimization: Identify and resolve performance bottlenecks, data quality issues, and other challenges that may arise during implementation and operation. Collaboration: Work closely with data engineers, data scientists, business analysts, and stakeholders to understand their needs and provide technical guidance. Innovation: Stay up-to-date with industry trends and emerging technologies to recommend innovative solutions that enhance our data analytics capabilities.