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Amazon Business Intelligence Engineer, GS S&O - T&C in San Francisco De Heredia, Costa Rica

Description

The AWS Training and Certification (T&C) organization educates customers, partners, and AWS employees on AWS services, products, and solutions. As part of the T&C Business Insights & Analytics team, you will design and develop scalable data and reporting solutions to provide actionable insights into the key performance indicators (KPIs) and metrics that drive the organization. We are seeking a talented Business Intelligence Engineer with experience in building reporting solutions to support the T&C business's data-driven decision-making.

Key job responsibilities

• Collaborate with business stakeholders to understand their data and reporting requirements, and translate them into effective BI solutions

• Design, develop, and maintain BI dashboards, reports, and visualizations using tools like Tableau, QuickSight, or similar

• Ensure the accuracy, integrity, and timeliness of data used in BI solutions by implementing robust ETL (Extract, Transform, Load) processes

• Contribute to the development and maintenance of the data warehouse and data modeling, ensuring an efficient and scalable BI data architecture

• Automate BI processes and workflows to improve efficiency and reduce manual effort

• Provide user support and training for BI tools and applications to the broader organization

• Continuously identify and implement enhancements to BI solutions based on feedback and changing business requirements

• Stay up-to-date with the latest BI trends, technologies, and best practices, and make recommendations for their adoption

• Effectively communicate BI findings and recommendations to stakeholders at various levels of the organization

About the team

About AWS

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Basic Qualifications

  • 5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience

  • Experience with data visualization using Tableau, Quicksight, or similar tools

  • Experience with data modeling, warehousing and building ETL pipelines

  • Experience in Statistical Analysis packages such as R, SAS and Matlab

  • Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

Preferred Qualifications

  • Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift

  • Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

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