Data Engineer, AWS Support S&O - ESSO - Strategy, Planning & Inspection (SPI)
Amazon Quicksight
Amazon Web Services
AWS
Aws Glue
Aws Iam
Big Data
Bigdata
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Integration
Data Lake
Data Pipeline
Data Platform
Data Processing
Data Warehouse
Database
Databases
EMR
Engineer
ETL
Firehose
Redshift
Reporting and Analytics
S3
SQL
Job Description
Amazon Web Services' Enterprise Support Strategy and Operations group, within the Strategy, Planning & Inspection (SPI) program, seeks a Data Engineer to design and maintain analytics infrastructure that enables data-driven decision making. This onsite role in Pittsburgh, PA partners with data scientists and business intelligence engineers to build dashboards and scalable data pipelines that turn large datasets into actionable insights.
Responsibilities
- Design, implement, and maintain a scalable analytical data platform to support reporting and analytics.
- Manage AWS resources such as EC2, EMR, S3, Glue, Redshift, and related services.
- Collaborate with cross-functional technology teams to extract, transform, and load data from diverse sources using SQL and AWS big data technologies.
- Evaluate and adopt new AWS technologies to expand capabilities and improve efficiency.
- Partner with Data Scientists and Business Intelligence Engineers to promote best practices in reporting and analytics.
- Continuously improve reporting and analytics processes, automating or simplifying self-service capabilities for customers.
Requirements
- Bachelor's degree required.
- Experience as a data engineer or in a related role such as software engineering, BI engineering, or data science, with a proven ability to manipulate and derive value from large datasets.
- At least three years of building and operating large-scale data structures for BI analytics, with strong SQL expertise.
- Experience providing technical leadership and mentoring engineers on data engineering best practices.
- Experience designing and operating highly available distributed data pipelines for extraction, ingestion, and processing of large data sets.
- Experience with data modeling, data warehousing, and building ETL pipelines.
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)
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