Business Intelligence Engineer, Data Center Capacity Delivery Tooling

Amazon Inc.; Seattle (WA); On-site; USD 120,000 - 180,000; Full time

Job summary

Amazon Data Services, Inc. seeks a Business Intelligence Engineer to drive data excellence for the Data Center Capacity Delivery Team. You will design data infrastructure, deliver reports, visualizations and automations to enable informed resourcing decisions.

The role requires strong data acumen with Redshift/Oracle/NoSQL, SQL and Python, plus the ability to partner with cross-functional teams. Build QuickSight dashboards and communicate insights across AWS.

Qualifications

• 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL
• Experience with SQL, ETL and statistical analysis
• Ability to communicate data insights clearly

Responsibilities

• Design, implement and support an analytical data infrastructure
• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
• Work closely with business partners and recruiting to support ongoing efforts
• Build automated data solutions in QuickSight
• Deep dive data to understand and resolve discrepancies
• Communicate actions/recommendations to customers/stakeholders in both written and verbal formats
• Create reports highlighting key insights and trends
• Create source-of-truth datasets using SQL; you leverage scripting language i.e. Python to create automation and reduce manual processes
• Partner with Data Engineering to enhance data infrastructure, data availability, and broad access to customer insights

Skills

Data analysis

SQL

ETL

Oracle

Redshift

NoSQL

Statistical analysis

Tools

QuickSight

Python

Job description

Business Intelligence Engineer, Data Center Capacity Delivery Tooling

Job ID: 10587820 | Amazon Data Services, Inc.

As a Business Intelligence Engineer (BIE), you will drive data excellence, provide data reporting, visualizations, automations, and insights for the Data Center Capacity Delivery Team. Candidates will be customer obsessed in their pursuit of data clarity and reporting. Successful candidates have track records of partnering with cross functional teams to create data alignment and visibility of data to enable businesses to make optimal resourcing decisions.

We are looking for someone with a broad background of data automation, strong business acumen, who takes ownership of their work, and is focused on customer needs. The successful candidate will communicate crisply to management. They will have an ability to make data-driven conclusions and will be comfortable with ambiguity while working in a fast-paced dynamic environment.

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on.

You’ll join a diverse team of project managers, construction managers, controls engineers, commissioning engineers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

Key job responsibilities

• Design, implement and support an analytical data infrastructure


• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers


• Work closely with business partners and recruiting to support ongoing efforts


• Build automated data solutions in QuickSight


• Deep dive data to understand and resolve discrepancies


• Communicate actions/recommendations to customers/stakeholders in both written and verbal formats


• Create reports highlighting key insights and trends


• Create source-of-truth datasets using SQL; you leverage scripting language i.e. Python to create automation and reduce manual processes


• Partner with Data Engineering to enhance data infrastructure, data availability, and broad access to customer insights

About the team

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.

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.

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.

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.

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.

Basic Qualifications

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


• 1+ years of SQL, ETL or Oracle experience


• 1+ years of processing large, multi-dimensional datasets from multiple sources experience


• 1+ years of performing statistical analysis experience