Data Engineer, AWS DC Central Operations

Amazon Web Services (AWS); Seattle (WA); On-site; USD 101,000 - 160,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Life & AD&D insurance

Job summary

Amazon Data Services, Inc. in Seattle is seeking a Data Engineer to enhance our data architecture and deliver end-to-end data engineering solutions for complex analytics.

You will collaborate with BI engineers and software engineers to translate data into actionable insights and support internal customers with reporting infrastructure. The role focuses on developing automated ETL pipelines, data modeling, and building scalable data warehouses/data lakes, while ensuring data security and proper

Qualifications

• 1 year of data engineering experience.
• Experience with data modeling, warehousing and building ETL pipelines.
• Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
• Experience with one or more scripting language (e.g., Python, KornShell)
• Preferred: Hadoop, Hive, Spark, EMR and ETL tools (Informatica, ODI, SSIS, BODI, Datastage).

Responsibilities

• 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.
• Implement and support reporting and analytics infrastructure for internal business customers.
• 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.
• Develop data objects for business analytics using data modeling techniques.
• Develop and optimize data warehouse and data lake tables using best practices for DDL, physical and logical tables, data partitioning, compression, and parallelization.
• Develop and maintain data warehouse and data lake metadata, data catalog, and user documentation for internal business customers.
• 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.

Skills

Data engineering

Data modeling

ETL pipelines

SQL

Scripting

Tools

Python

KornShell

Spark

HiveQL

SparkSQL

Job description

Description

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. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

As a Data Engineer on our team, you'll work with technologies and complex data environments. You'll be responsible for enhancing our existing data architecture to further standardize metrics and definitions, developing end-to-end data engineering solutions for complex analytical problems, and collaborating with business intelligence engineer, and software engineers to translate data into actionable insights.

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

• 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.
• Implement and support reporting and analytics infrastructure for internal business customers.
• 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.
• Develop data objects for business analytics using data modeling techniques.
• Develop and optimize data warehouse and data lake tables using best practices for DDL, physical and logical tables, data partitioning, compression, and parallelization.
• Develop and maintain data warehouse and data lake metadata, data catalog, and user documentation for internal business customers.
• 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.

A day in the life

Imagine a Day Where You're Not Just Managing Data, But Crafting Intelligent Systems That Tell Compelling Stories. You'll Dive Into Intricate Data Landscapes, Designing Pipelines That Seamlessly Connect AWS Data Center Datasets, Optimize Performance, And Unlock Hidden Patterns. Your Work Will Involve

• Exploring innovative data transformation techniques
• Developing intelligent, automated reporting solutions
• Collaborating with cross-functional teams to solve complex analytical challenges
• Researching emerging technologies that could revolutionize our data strategy

About The Team

BASIC QUALIFICATIONS

• 1 years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
• Experience with one or more scripting language (e.g., Python, KornShell)

Preferred Qualifications

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

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, Seattle - 101,300.00 - 160,000.00 USD annually

Company - Amazon Data Services, Inc.

Job ID: A10519392