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Business Intelligence Engineer, ProdOps OAT, Leo

Amazon

Business Intelligence Engineer, ProdOps OAT, Leo

Amazon

Bellevue, WA, USA

·

On-site

·

Full-time

·

1mo ago

Compensation

$89,600 - $89,600

Benefits & Perks

Professional development budget

Comprehensive health, dental, and vision insurance

Competitive salary and equity package

Flexible work arrangements

Learning

Healthcare

Equity

Flexible Hours

Required Skills

Python

JavaScript

TypeScript

Leo is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity.
Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

Role Overview:

As a Business Intelligence Engineer (BIE), you will implement and maintain effective analytics solutions that drive data-informed decisions to streamline the production of Leo's satellite technology. You will focus on creating efficient, maintainable, and well-documented processes for data analysis and reporting.
As a BIE within Leo Prod Ops, you will tackle complex data challenges and translate them into clear, actionable insights for the business. You are a customer-obsessed problem-solver who will build effective partnerships across Leo's ecosystem, including hardware, software, supply chain, manufacturing, launch, facilities, transportation, and finance teams. Your ability to invent and simplify processes will be key to solving day-to-day data needs. You will use your communication skills to articulate data concepts clearly and collaborate with diverse technical and non-technical stakeholders to deliver results. You will contribute to the team's engineering excellence by implementing best practices and proactively seeking opportunities to learn and share knowledge.

  • Key job responsibilities
  • Collaborate with cross-functional and cross-organizational teams to understand business needs and implement data-driven solutions that enable better decision making
  • Define and track key metrics and performance indicators to monitor performance and drives continuous improvement across Leos's operations.
  • Execute analytical approaches to uncover new insights and share recommendations that improve productivity
  • Design and build robust, self-service reporting solutions that scale across the organization
  • Write complex, performant SQL queries and develop efficient data pipelines to support both recurring and ad-hoc analytical needs
  • Build and maintain data infrastructure in collaboration with BIEs/DEs, focusing on improving data quality and availability
  • Communicate analytical findings and methodology to diverse stakeholders through clear documentation and presentations
  • Lead technical initiatives and actively share knowledge with team members, supporting analytics best practices
  • Maintain awareness of AI/ML advancements (especially around LLMs and GenAI) and propose new technologies for team consideration
    A day in the life
    This role will be highly collaborative, requiring partnerships with cross-functional leaders to drive positive results. You will tackle challenging, novel business problems every day and have the opportunity to work with multiple technical teams of Leo. You should be comfortable with a high degree of ambiguity and relish the idea of solving problems that haven't been solved at scale before. Along the way, we guarantee that you will learn a lot, have fun and make a positive impact on millions of people.
    About the team
    The Operations Analytics Team (OAT) was established to develop end-to-end analytics products across Leo Production Operations (Prod Ops). This includes both tools and insights for Prod Ops leadership and functional teams. OAT products are leveraged as the single-source-of-truth for insights and metrics that production teams rely on to drive performance. OAT works in parallel with the Leo Production PMO to coordinate actions and release analytics products across all Leo teams.

Basic Qualifications

  • Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field
  • 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
  • 3+ years of BIE or similar role experience with writing complex, highly-optimized SQL queries across large datasets
  • 3+ years experience with data visualization using Tableau, Quick Suite, Grafana, or similar tools
  • 3+ years experience with data modeling, warehousing and building ETL pipelines
  • Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
  • Experience in Statistical Analysis packages such as R, SAS and Matlab

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
  • Experience with forecasting and statistical analysis
  • Master's degree in sciences, engineering, finance or equivalent
    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.
    Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $89,600/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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About Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

Employees

Seattle

Headquarters

Reviews

2.9

10 reviews

Work Life Balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a Friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

2 data points

L2

L3

L4

L5

L6

M3

M4

M5

M6

L2 · Product Designer L2

0 reports

$163,720

total / year

Base

$65,488

Stock

$81,860

Bonus

$16,372

$114,604

$212,836

Interview Experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer Rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge