Data Engineer, Data : Science Engineering, AWS Marketing, Data : Science Engineering, AWS Marketing, TAA-Data: Science & Engineering

Would you like to support increasing the customer base and revenue for AWS, a market-leading cloud offering? Join a team focused on increasing awareness and adoption of the AWS platform by analyzing customer behavior on and outside AWS websites. Empower the AWS Marketing organization to make data-driven decisions that further establish AWS as a leader in the cloud computing world.

About the role

As a Data Engineer at AWS, you will work in a large, complex, and dynamic data warehousing environment. You will integrate multiple heterogeneous data sources with the AWS Marketing Data Warehouse (Jarvis) and build efficient, flexible, and scalable data warehouse and reporting solutions. You will implement solutions using new technologies to enable upgrades of the existing platform. You will collaborate with business owners to develop and define key business questions and build datasets to answer them. You will design, implement, and operate stable, scalable, low-cost solutions to flow data from production systems into the data warehouse and into end-user reporting applications. You will own a core segment of a growing marketing platform serving thousands of internal customers and millions of external customers, building on multiple AWS services and engaging directly with those teams to improve core offerings.

Responsibilities

• Design, implement, and support a platform providing ad-hoc access to large datasets
• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL
• Build robust and scalable data integration (ETL) pipelines using SQL, Python, and AWS services such as Data Pipelines and Glue
• Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL/Redshift
• Interface with business customers, gathering requirements and delivering complete reporting solutions
• Build and deliver high-quality datasets to support business analyst and customer reporting needs
• Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers

About the team

The Sales, Marketing, and Global Services (SMGS) team at AWS drives revenue, adoption, and growth from small and mid-market accounts to enterprise-level customers, including the public sector. The AWS Global Support team partners with leading companies to ensure customer success.

The AWS Marketing Data: AI Science, Analytics, and Engineering (D:SE) team owns analytics, reporting, self-service tooling, data representation, machine learning models, measurement, valuation, and economics products for AWS Marketing. As the central data and science organization, we work with different AWS Marketing teams to improve measurement, increase experimentation velocity, enhance data access and analytical self-service, deploy and test ML-powered targeting models, and empower strategic decisions. We establish standards, benchmarks, and best practices globally for AWS Marketing.

Requirements

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

Preferred Qualifications

• Experience with big data technologies such as Hadoop, Hive, Spark, and EMR
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

Pay

Base salary range: $101,300.00 - $160,000.00 USD annually. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on experience, qualifications, and location.

Benefits

• Comprehensive health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, and optional supplemental life plans)
• Employee Assistance Program (EAP) and Mental Health Support
• Medical Advice Line
• Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off and parental leave