We are looking for a passionate Business Intelligence Engineer to join a growing BI team in the AWS Support Commercial Product organization to help inform the direction of AWS Support and Amazon Managed Services through data, at scale.
The successful candidate will have strong Business Analytics skills, be comfortable using SQL to identify KPIs to drive business growth, analyzing data to inform strategic and tactical initiatives, and write up findings for less-technical audiences.
Strong SQL (any implementation) is a must. Experience in Finance or Accounting is preferable.
This is a highly visible role that partners with Product Management, Marketing, Finance, and other stakeholder teams.
Key job responsibilities
- Manipulate / mine data from database tables (ex. Redshift) using SQL and ETL
- Provide concise and accurate written updates on business health and trends
- Develop analytical tools : deep-dive tools, UIs, metrics, and dashboards
- Perform deep-dives and root cause analysis to answer business questions
- Work with cross functional stakeholders in defining the source of truth and obsessively making sure the data fidelity is high
- Effectively communicate (written and verbal) solutions and methodologies to senior leadership
- Work with engineering teams to enable the appropriate capture and storage of data
- Complete ad hoc data retrieval and analysis
- Monitor existing metrics, develop and propose new metrics, and identify new, actionable risk signals
About the team
The AWS Premium Support product team manages the strategy for AWS's Support and Managed Service Offerings. The team is responsible for defining new support and managed services products, customer experiences, pricing, and financial business health.
We keep iterating on products and services to help customers achieve their goals on AWS.
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred 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.
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 flexible work hours and arrangements are part of our culture.
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Inclusive Team Culture
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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 and 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.
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.
The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success.
AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.
BASIC QUALIFICATIONS
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with forecasting and statistical analysis
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience writing complex SQL queries
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
- Strong background in Finance / Accounting