Data Engineer, AWS GDSP A&I

Amazon Web Services (AWS) is a dynamic and rapidly growing business within Amazon, providing innovative services that help organizations scale and grow. The Data Engineer role focuses on building scalable analytical solutions to support the Private Pricing Program, driving efficiency in data handling processes and collaborating with various teams to deliver actionable insights.

Responsibilities

• Design, develop, and maintain scalable data solutions for metrics, reports, analyses, and dashboards that support analytical and business needs
• Collaborate with technology teams to extract, transform, and load data from diverse sources using AWS services and internal tools
• Build and deliver high-quality datasets that support data science initiatives and customer reporting requirements
• Automate and optimize reporting processes to enable self-service analytics for stakeholders
• Translate business problem statements into technical analysis requirements
• Apply analytical and statistical rigor to answer business questions and drive data-driven decisions
• Develop measurement frameworks that quantify customer experience and drive business outcomes
• Create queries and visualizations for ad-hoc requests, projects, and ongoing reporting needs
• Write efficient, optimized queries with deep knowledge of data structures and query optimization techniques
• Adopt best practices in reporting and analysis including data integrity, design, validation, and documentation
• Troubleshoot operational data quality issues and audit existing data pipelines and queries
• Recommend improvements to back-end data sources for increased accuracy and simplicity

Preferred

• 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)
• AWS Redshift
• AWS S3
• AWS Glue
• AWS EMR
• AWS Kinesis
• AWS FireHose
• AWS Lambda
• IAM roles
• Non-relational databases
• Object storage
• Document stores
• Key-value stores
• Graph databases
• Column-family databases

Benefits

• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and 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

Company

• Online retail and cloud computing services
• Seattle, Washington, USA
• https://amazon.com/
• Founded in 1994
• 10001+ employees

Qualifications

• 3+ years of data engineering experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience
• Experience with data modeling, warehousing and building ETL pipelines
• 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)

Required skills

• AWS EMR, AWS FireHose, AWS Glue, AWS IAM, AWS Kinesis, AWS Lambda, AWS Redshift, AWS S3, Data Engineering, Data Modeling, Data Warehousing, ETL/ELT processes, Non-relational databases, OLAP technologies, Oracle, SQL

Preferred skills

• Attention to detail, Communication, Creativity, Prioritization, Self-starter

Experience

• 3+ years