Data Engineer II, AWS Infrastructure Supply Chain Automation

Amazon; Seattle (WA); On-site; USD 118,000 - 206,000; Full time

Job summary

An established industry player is seeking a skilled Data Engineer to join their dynamic team focused on AWS Infrastructure. In this role, you will be responsible for developing and maintaining automated ETL pipelines, utilizing a range of AWS services to enhance data management and analytics capabilities. You will collaborate with a diverse group of professionals, driving critical improvements through data-driven decision-making. This innovative firm fosters an inclusive culture where your ideas can flourish and contribute to the success of multi-billion dollar operations. If you are passionate about leveraging data to solve complex business challenges, this opportunity is perfect for you.

Benefits

Medical Insurance

401(k) Plan

Employee Discounts

Paid Time Off

Flexible Work Hours

Equity Options

Training and Development Programs

Qualifications

• 4+ years of experience in data engineering with a focus on ETL and data modeling.
• Proficient in Python, SQL, and AWS technologies for data solutions.

Responsibilities

• Develop and maintain automated ETL pipelines using Python and AWS services.
• Implement reporting and analytics infrastructure for internal business customers.
• Ensure data security and permissions for enterprise scale data solutions.

Skills

Data Engineering

ETL Pipelines

Data Modeling

Python

SQL

Spark

AWS Services

Education

Bachelor's Degree in Computer Science or related field

Tools

AWS Redshift

AWS Glue

AWS Lambda

AWS S3

AWS EMR

AWS Kinesis

AWS CloudWatch

Job description

Data Engineer II, AWS Infrastructure Supply Chain Automation

Job ID: 2960838 | Amazon.com Services LLC

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. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, 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. You’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

We’re looking for Data Engineers to help us grow our Data Lake and Data Warehouse Systems, which is being built using a serverless architecture, with 100% native AWS components including Redshift Spectrum, Athena, S3, Lambda, Glue, EMR, Kinesis, SNS, CloudWatch and more! We own a world-class data lake that is used to drive multi-billion dollar decisions on a regular cadence and we're looking to improve on filling the lake quickly, with as little human intervention needed and democratize the data in the lake.

Our Data Engineers build the ETL and analytics solutions for our internal customers to answer questions with data and drive critical improvements for the business. Our Data Engineers use best practices in software engineering, data management, data storage, data compute, and distributed systems. We are passionate about solving business problems with data!

Key job responsibilities

1. Develop and maintain automated ETL pipelines (with monitoring) using scripting languages such as Python, Spark, SQL and AWS services such as S3, Glue, Lambda, SNS, SQS, KMS.
2. Implement and support reporting and analytics infrastructure for internal business customers.
3. Develop and maintain data security and permissions solutions for enterprise scale data warehouse and data lake implementations including data encryption and database user access controls and logging.
4. Develop data objects for business analytics using data modeling techniques.
5. Develop and optimize data warehouse and data lake tables using best practices for DDL, physical and logical tables, data partitioning, compression, and parallelization.
6. Develop and maintain data warehouse and data lake metadata, data catalog, and user documentation for internal business customers.
7. Work with internal business customers and software development teams to gather and document requirements for data publishing and data consumption via data warehouse, data lake, and analytics solutions.

BASIC QUALIFICATIONS

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

PREFERRED QUALIFICATIONS

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

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 this link for more information.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,900/year in our lowest geographic market up to $205,600/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 this link.