Amazon.com Services LLC
Business Intelligence, Data Engineering, pxt
DataEngineer,Compensation
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Engineer, Compensation at Amazon.com Services LLC. Skills: Data engineering, Data warehousing, ETL, AWS. Lead the modernization of one of compensation data. Architect scalable data infrastructure solutions”
What You'll Achieve.
Drive for best-in-class analytics; Drive for dashboard design; Drive for new innovative approaches; Deliver analytics and insights that drive day-to-day decision-making
Industry & Context.
Solving challenging, ambiguous problems
What They're Looking For.
Must Have
5+ years of data engineering experience, Experience with data modeling, Experience with warehousing, Experience building ETL pipelines, Experience with SQL, Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, Finance or related field, Hands on experience with Python/Scala, Writing complex data transformations in spark, Automating pipelines, Comfortable using AWS services such as EMR(Hive/Spark), Redshift, S3, Glue, Cloudformation, Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
Nice to Have
Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions, Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
What You'll Do.
Lead the modernization of one of compensation data
Architect scalable data infrastructure solutions
Partner with business
and data science teams
Deliver analytics and insights
Build end-to-end systems from ideation
experimentation through production
Design and implement AI agents that automate complex
Work directly with customer teams to identify automation
Own the full project lifecycle: data pipelines
Gather requirements for data logging
Design scalable solutions for metadata management
Implement scalable solutions for metadata management
Support scalable solutions for metadata management
Design data pipeline orchestration
Implement data pipeline orchestration
Support data pipeline orchestration
Design data modelling
Implement data modelling
Support data modelling
Design data visualization
Implement data visualization
Support data visualization
Manage data infrastructure
Build automated CDK based solution
How You'll Work.
Team & Collaboration
Partner with business teams; Partner with product teams; Partner with data science teams; Work with stakeholders
Process & Methodology
Project lifecycle
Full Job Description
Amazon Compensation Data team is looking for Data Engineer (DE) to join our team for modernizing data warehouses serving business intelligence, data science and AI customers globally. Your role will involve designing, implementing, and supporting scalable solutions for metadata management, data pipeline orchestration, ETL, data modelling and data visualization with the tools available from AWS – including Sage Maker Unified Studio, Redshift, Glue, S3, IAM, Cloudwatch, and Apache Airflow. As DE you will be managing data infrastructure ,building automated CDK based solution. You will work with stakeholders to gather requirements for data logging,storing,transforming and reporting. The ideal candidate will be passionate about working with big data sets and have the expertise to utilize these datasets to answer business questions and drive for best-in-class analytics, dashboard design and new innovative approaches.The ideal candidate will be entrepreneurial and innovative, thriving on solving challenging, ambiguous problems Key job responsibilities Lead the modernization of one of compensation data warehouses serving customers globally. As a Data Engineering, you'll architect scalable data infrastructure solutions, partner with business, product, and data science teams to deliver analytics and insights that drive day-to-day decision-making across the organization. A day in the life What you'll do: Build end-to-end systems from ideation, experimentation through production deployment Design and implement AI agents that automate complex decisions Work directly with customer teams to identify automation opportunities and measure impact Own the full project lifecycle: data pipelines, deployment, and monitoring Basic Qualifications: - 5+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with SQL - Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, Finance or related field. - Hand
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