Data Engineer, AWS Support S&O - ESSO - Strategy, Planning & Inspection (SPI)

The Data Engineer supporting AWS Enterprise Support Strategy and Operations designs and maintains analytics infrastructure to enable key metrics, dashboards, and data-driven decisions. The role collaborates with data scientists and BI engineers, leveraging SQL, Redshift and Quicksights to deliver actionable insights across SPI operations.

Overview

Within the Strategy, Planning and Inspection group, the Data Engineer builds scalable data architectures, develops and sustains data pipelines, and curates dashboards that inform strategic and operational decisions. The position emphasizes SQL driven analytics using Redshift and Quicksights, with a strong focus on collaborating with Data Scientists and BI Engineers to promote best practices in reporting and analysis.

Location

Pittsburgh, PA (onsite)

Salary

USD 132,100 - 178,800 per yearly

Responsibilities

• Architect, implement, and maintain an analytics data platform to support reporting and analysis.
• Administer AWS services such as EC2, EMR, S3, Glue, Redshift, and related infrastructure.
• Collaborate with cross-functional technology teams to extract, transform, and load data from diverse sources using SQL and AWS big data technologies.
• Continuously explore new AWS technologies to introduce capabilities and improve efficiency.
• Partner with Data Scientists and BI Engineers to identify and promote best practices in reporting and analytics.
• Enhance ongoing reporting and analytics workflows, automating or simplifying self-service options for customers.

Requirements

• Bachelor's degree.
• Experience as a data engineer or related role (eg software engineer, BI engineer, data scientist) with a track record of manipulating, processing, and deriving value from large datasets.
• 3+ years developing and operating large-scale data structures for business intelligence analytics using SQL.
• 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 ETL pipeline development.

Technologies

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

Benefits

• Health insurance
• 401(k) matching
• Paid time off
• Parental leave
• Sign-on payments
• Restricted stock units (RSUs)