Data Engineer

This onsite Data Engineer role is based in Seattle, WA, on the AWS Infrastructure Services team within Amazon Data Services, Inc. It focuses on building and maintaining ETL pipelines, developing data architectures, and delivering analytics solutions for internal customers, in collaboration with BI engineers and software teams to standardize metrics and drive insights.

Responsibilities

• Build and operate automated ETL pipelines with integrated monitoring, using Python, Spark, SQL and AWS services such as S3, Glue, Lambda, SNS, SQS, and KMS.
• Design and support reporting and analytics infrastructure for internal stakeholders.
• Create and manage data security and access controls for enterprise scale data warehouses and data lakes, including encryption, user permissions, and audit logging.
• Create data assets for analytics using established data modeling techniques.
• Design and optimize data warehouse and data lake tables, applying best practices for DDL, physical and logical structures, partitioning, compression, and parallelization.
• Maintain metadata, data catalogs, and user documentation for data warehouses and data lakes to assist internal users.
• Collaborate with internal stakeholders and software teams to gather and document requirements for data publishing and consumption across data warehouses, data lakes, and analytics solutions.

Requirements

• 1+ years of experience in data engineering
• Experience with data modeling, data warehousing, and building ETL pipelines
• Experience with at least one query language, such as SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, or Scala
• Experience with at least one scripting language, such as Python or KornShell

Technologies

• Python
• Spark
• SQL
• S3
• Glue
• Lambda
• SNS
• SQS
• KMS
• Hadoop
• Hive
• EMR
• Informatica
• ODI
• SSIS
• BODI
• Datastage

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription), Basic Life and AD&D insurance with 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
• Parental leave

A Day in the Life

• Investigating advanced data transformation approaches
• Designing and deploying automated reporting solutions
• Partnering with cross-functional teams to address complex analytics challenges
• Evaluating emerging technologies to enhance the data strategy