热门公司

招聘

职位Amazon

BIE II, ShipTech Analytics, ShipTech Analytics

Amazon

BIE II, ShipTech Analytics, ShipTech Analytics

Amazon

Hyderabad, TS, IND

·

On-site

·

Full-time

·

1w ago

Do you want to be in the forefront of engineering big data analytical solutions that takes Amazon's global transportation models to the next generation? Do you have a solid analytical thinking, metrics driven decision making and want to solve problems with solutions that will meet the growing worldwide need? We are looking for top notch Business Intelligence Engineers to be part of Ship Tech Analytics team to build data and analytics solutions powering Amazon's global transportation network. We perform data modeling, build real time analytical platforms using big data tools and AWS technologies like Hadoop, Spark, EMR, SNS, SQS, Lambda, Kinesis Firehose, DynamoDB Streams.

As a BIE II, you'll work on building analytical solutions that empower operations teams worldwide. You'll develop both near-real-time (NRT) streaming pipelines and batch processing pipelines that deliver critical insights for decision-making. You'll also build metrics for the transportation network, while contributing to innovative AI-powered solutions delivering automated insights across the transportation network.

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. The candidate is a self-starter, comfortable with ambiguity, able to think big (while paying careful attention to detail), and enjoys working in a fast-paced and global team. We're excited to talk to those up to the challenge!

  • Key job responsibilities
  • Design, develop and implement dashboards, metrics, KPIs and analytical reports to drive key business decisions supporting Amazon's global transportation network
  • Partner with business stakeholders across operations and analytics teams to gather business requirements and translate into technical solutions
  • Collaborate with technology teams to extract, transform, and load data from a wide variety of data sources using SQL and ETL tools
  • Build and deliver high quality data pipelines to support data engineers, business analyst, data scientists, and customer reporting needs
  • Combine knowledge of statistical methodology and analysis with programming skills to support complex business problems
  • Continually improve ongoing reporting and analysis processes, automating analytical pipelines and build AI-powered solutions
  • Implement training and documentation solutions that enable business stakeholders to get the most out of our self-serve reporting tools
  • Must possess solid verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment
  • Enjoy working closely with your peers in a group of smart and talented engineers

About the team
Ship Tech Analytics serves as the data and analytics backbone for Amazon's global transportation network. The team builds standardized data solutions that streamline analytics and enable faster decision-making for operations teams worldwide. Team members collaborate with cross-functional partners to deliver data products and tools.

The team is modernizing systems, building near-real-time architectures, and building AI-powered automation. Team members have opportunities to mentor others, prototype new ideas , and shape the future of the data analytics. The team values collaboration across geographies with members in multiple locations working together to serve global operations.

Basic Qualifications

  • 3+ 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 using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
  • Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
  • Experience working directly with business stakeholders to translate between data and business needs

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

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.

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关于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+

员工数

Seattle

总部位置

$1.5T

企业估值

评价

2.9

10条评价

工作生活平衡

2.8

薪酬

3.7

企业文化

2.5

职业发展

2.3

管理层

2.1

35%

推荐给朋友

优点

Good pay and compensation

Strong benefits package

Flexible scheduling options

缺点

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

薪资范围

4个数据点

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0份报告

$108,330

年薪总额

基本工资

$43,332

股票

$54,165

奖金

$10,833

$75,831

$140,829

面试经验

10次面试

难度

3.7

/ 5

时长

21-35周

录用率

20%

体验

正面 10%

中性 10%

负面 80%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge