Data Engineer

Join Amazon Web Services in Dallas, onsite. This Data Engineer role offers a competitive annual salary ranging from USD 132,100 to 178,800, along with comprehensive benefits and a culture that emphasizes collaboration and data‑driven decision making. You will design, build, and maintain analytic data infrastructure, develop metrics and dashboards, and empower teams to make informed choices.

Benefits

• Medical, dental, and vision insurance with prescription coverage, plus Basic Life and AD&D protection and the option for supplemental life plans
• Employee Assistance Program (EAP) with mental health support and access to a Medical Advice Line
• Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave

Responsibilities

• Design, build, and maintain scalable analytical data infrastructure to support analytics
• Manage AWS resources including EC2, EMR, S3, Glue, Redshift, and related services
• Collaborate with cross-functional teams to extract, transform, and load data from diverse sources using SQL and AWS big data tools
• Continuously evaluate and adopt new AWS technologies to unlock capabilities and boost efficiency
• Partner with data scientists and BI engineers to establish and promote reporting and analysis best practices
• Drive improvements in reporting and self-service analytics by automating processes and simplifying access for customers

Requirements

• Bachelor's degree
• Experience as a data engineer or related specialty (software engineer, BI engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets
• At least 3 years developing and operating large-scale data structures for BI analytics, with strong SQL experience
• Experience providing technical leadership and mentoring other engineers on data engineering best practices
• Experience building and operating highly available, distributed systems for data extraction, ingestion, and processing of large data sets
• Experience with data modeling, warehousing, and building ETL pipelines

Technologies

• SQL
• Redshift
• Quicksights
• AWS Glue
• EMR
• S3
• EC2
• IAM
• Kinesis
• FireHose
• Lambda