Data Analyst

- Previous working experience in comparable data engineering or business intelligence role,
- Advanced proficiency in SQL and experience with big data technologies,
- Strong knowledge of data warehousing concepts and dimensional modeling (e.g., designing fact and dimension tables, implementing slowly changing dimensions, schema design, table key design, and data denormalization techniques),
- Expertise in AWS services for data pipelines and analytics (e.g., Redshift, Glue, EMR, S3, Lambda, API Gateway),
- Experience with data visualization tools (e.g., QuickSight),
- Solid understanding of data security principles,
- Excellent communication skills, with the ability to convey complex technical information to diverse audiences.
- AWS certifications (e.g., AWS Certified Cloud Practitioner) or equivalent hands-on experience
- Experience with Amazon's internal technologies and data ELT platforms,
- Proficiency in programming languages such as Python or Java,
- Familiarity with machine learning concepts and tools (e.g., SageMaker),
- Strong problem-solving skills and ability to work in a fast-paced environment,
- Experience working in cross-functional teams and collaborating with various stakeholders,
- Bachelor's Degree in Computer Science, Software Engineering, or a related technical field.

Acknowledgement of country:
In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community. We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.

IDE statement:
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer, and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected attributes.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Amazon is rapidly expanding in Australia. We continue to invest heavily in the creation of a best in class delivery network to delight Australians with amazing customer experiences. Data is at the heart of everything we do and it’s especially critical to the success of our logistics teams in their quest to deliver your goods to you faster than ever before. To do so we have created the exciting position of Data Analyst.

Amazon's AU Delivery Service team is seeking a skilled Data Analyst to build and own end-to-end data pipeline automation and metric reporting processes that optimize our local logistics operations and drive customer-centric decisions.

At Amazon, we're driven by data. Our vast global infrastructure generates an unprecedented volume of data daily, requiring secure and innovative engineering solutions to organize, automate, and optimize for our local AU operations. As both a data producer and consumer, you'll be an expert in Amazon's data ecosystem, building data models and ensuring timely data availability using AWS tools and other Amazon's internal technologies.

Key Job Responsibilities:
- Collaborating with stakeholders to gather requirements and formulate problems into data solutions,
- Working closely with cross-functional teams, communicating effectively with both technical and non-technical stakeholders,
- Architecting and implementing scalable data pipelines and reporting processes using AWS services and Amazon's internal ETL tools,
- Applying best practice in access permissions and security controls for data and applications,
- Creating and optimizing data models to support business insights and decision-making,
- Developing and enhancing dashboards,
- Mapping datasets to operation and business processes,
- Serving as a subject-matter expert on Amazon's data ecosystem,
- Developing standardized approaches to handle market-specific data nuances while maintaining global consistency,
- Maintaining critical documentation.