Senior Business Intelligence Engineer, ShipTech Analytics
AI in this role
Build big data analytical solutions, ETL pipelines, and AI-powered automation to optimize global transportation networks.
As a BIE, you'll work on building analytical solutions that empower operations teams worldwide. The ideal candidate relishes working with large volumes of data, enjoys the challenge of highly complex technical contexts, and, above all else, is passionate about data and analytics. The candidate is an expert with data modeling, ETL design and business intelligence tools and passionately partners with the business to identify strategic opportunities where improvements in data infrastructure creates out-sized business impact and is a self-starter, comfortable with ambiguity, able to think big, and enjoys working in a fast-paced and global team. The candidate will also build metrics for the transportation network, while contributing to innovative AI-powered solutions delivering automated insights across the transportation network.
Key job responsibilities
1. Design and build scalable ETL and metrics supporting Amazon's global transportation network.
2. Build data reporting and data tools that streamline the complete business lifecycle
3. Partner closely with stakeholders across operations and analytics teams to understand requirements, design solutions, and deliver metrics and insights that enable faster, more informed decision-making
4. Own data quality and implement enhancements for datasets that enable operational excellence and improve customer experience
5. Collaborate with cross-functional teams to standardize analytics capabilities and build AI-powered automation
6. Leverage AWS cloud technologies to transform raw data into actionable metrics
7. Drive continuous improvement through code reviews, design discussions, and operational best practices
8. Partner with senior engineers and principal engineers to solve problems at scale to improve existing data services, building new ones, that enhance customer experience
Basic qualifications
- 5+ years of professional or military experience
- 5+ years of SQL experience
- 4+ years of processing large, multi-dimensional datasets from multiple sources experience
- 1+ years of performing statistical analysis experience
- 5+ years of as a Data Analyst, Data Engineer, Business Intelligence Analyst, or a related occupation experience
- 5+ years of using SQL, ETL (Extract, Transform, Load), or Oracle experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field
- Experience programming to extract, transform and clean large (multi-TB) data sets
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
- Experience working directly with business stakeholders to translate between data and business needs
Preferred qualifications
- Experience managing, analyzing and communicating results to senior leadership
- Experience with AWS technologies
- Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices
- Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Bellevue - 130,400.00 - 176,300.00 USD annually
How we score this
Senior Business Intelligence Engineer, ShipTech Analytics at Amazon scores 65 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.
AI Level 3. The daily work is on or around AI systems, without necessarily building the model: remove AI and the job is hollow.
- AI Level 480 to 100
- AI Level 360 to 79
- AI Level 240 to 59
- AI Level 10 to 39
Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where data modeling was part of your work. What did you do?
- Tell me about a project where business intelligence was part of your work. What did you do?
- Tell me about a project where big data was part of your work. What did you do?
- Tell me about a project where analytics was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Etl, Data Modeling, Business Intelligence, Big Data, and Analytics. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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