Data Engineer II, Business Data Technologies

Amazon.com Services LLC; Seattle (WA); On-site; USD 132,000 - 179,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Sign-on payments

RSUs

Job summary

Amazon.com Services LLC is hiring a Data Engineer II to build and operate large-scale data structures for analytics and deep learning in a high-volume data environment.

The role emphasizes real-time and batch data ingestion, ETL/ELT best practices using AWS and big data tools, and an end-to-end development lifecycle. Mentoring junior data engineers is also part of the role. Onsite location in Seattle, WA.

Qualifications

• 3+ years of data engineering experience.
• Experience with data modeling, warehousing, and building ETL pipelines.

Responsibilities

• Design, develop, implement, test, and operate large-scale, high-volume data structures for analytics and deep learning.
• Build real-time and batch data ingestion routines using data modeling and ETL/ELT best practices with AWS and big data tools.
• Collect business and functional requirements and translate them into robust, scalable, operable solutions aligned with the overall data architecture.
• Analyze source data systems and drive best practices within source teams.
• Own the end-to-end development lifecycle, including design, implementation, testing, documentation, delivery, support, and maintenance.
• Create comprehensive, usable dataset documentation and metadata.
• Evaluate and decide on dataset implementations proposed by peer data engineers.
• Evaluate and decide on the use of new or existing software products and tools.
• Mentor junior data engineers

Skills

Data engineering

Data modeling

Data warehousing

ETL pipelines

Mentoring

Tools

AWS

Amazon Redshift

Hive

Apache Spark

Amazon EMR

RDBMS

Amazon S3

AWS Glue

Amazon Kinesis

Kinesis Firehose

AWS Lambda

IAM

Job description

Amazon eCommerce Foundation’s Business Data Technologies team is hiring a Data Engineer II to build and operate large-scale data structures for analytics and deep learning in a high-volume data environment.

Responsibilities

• Design, develop, implement, test, and operate large-scale, high-volume, high-performance data structures for analytics and deep learning
• Build real-time and batch data ingestion routines using data modeling and ETL/ELT best practices with AWS and big data tools
• Collect business and functional requirements and translate them into robust, scalable, operable solutions aligned with the overall data architecture
• Analyze source data systems and help drive best practices within source teams
• Own the end-to-end development lifecycle, including design, implementation, testing, documentation, delivery, support, and maintenance
• Create comprehensive, usable dataset documentation and metadata
• Evaluate and make decisions on dataset implementations proposed by peer data engineers
• Evaluate and make decisions on the use of new or existing software products and tools
• Mentor junior data engineers

Requirements

• 3+ years of data engineering experience
• Experience with data modeling, warehousing, and building ETL pipelines

Technologies

• AWS
• Amazon Redshift
• Hive
• Apache Spark
• Amazon EMR
• RDBMS
• Amazon S3
• AWS Glue
• Amazon Kinesis
• Kinesis Firehose (FireHose)
• AWS Lambda
• IAM roles and permissions
• Real-time and batch ingestion
• ETL/ELT
• Non-relational databases / data stores
• Object storage
• Document or key-value stores
• Graph databases
• Column-family databases

Benefits

• Health insurance (medical, dental, vision, prescription; Basic Life & AD&D; Supplemental life options; EAP; Mental Health Support; Medical Advice Line; Flexible Spending Accounts; Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• Paid time off
• Parental leave
• Sign-on payments
• Restricted stock units (RSUs)

Preferred Qualifications

• Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with non-relational databases / data stores including object storage, document or key-value stores, graph databases, and column-family databases

About the Team

• BDT collects petabytes of data from thousands of sources inside and outside Amazon, including the Amazon catalog system, inventory system, customer order system, page views, and Alexa systems
• Supports Amazon subsidiaries such as IMDB and Audible
• Enables internal customers to access and query data hundreds of thousands of times per day using AWS Redshift, Hive, and Spark
• Builds scalable solutions that grow with the Amazon business

Role Context

• Amazon’s eCommerce Foundation (eCF) organization is responsible for core components driving the Amazon website and customer experience
• In this role, you will design, develop, implement, test, and operate data structures for analytics and deep learning in a cloud-based data lake

Location: Seattle, WA (onsite) | Experience: 3+ years | Salary: USD 132,100 - 178,800 per year