Data Streaming Engineer Jobs

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1d ago

Data Engineer, Data Infrastructure and Generative Intelligence - AIGC Finance

Amazon.com Services LLC New York, NY

New York, NY

1d ago

$145k - $197k/yr Full time Amazon Web Services Analytics Artificial Intelligence

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Job Description

As a Data Engineer within Amazon Ads’ AIGC DIGI Finance team, you will help re-envision and build analytical data infrastructure that supports multiple ads businesses. The role partners with Finance and business leaders to deliver scalable, stable, and accurate data solutions while working closely with engineering teams on ETL/ELT, data modeling, and warehousing.

Responsibilities

Assess distinct business needs and review the current technology stack and data landscape; design, re-design, implement, and build an analytical data infrastructure for multiple ads businesses
Coordinate with upstream and partner data teams to support reliable data solutions for the team
Manage AWS resources including EC2, EMR, S3, AWS Glue, and Amazon Redshift
Interface with other technology teams to extract, transform, and load data from a wide range of data sources
Explore, learn, and adopt current AWS technologies to introduce capabilities and improve operational efficiency
Collaborate with and support Business Intelligence Engineers (BIEs) on best practices for reporting and analysis, including data integrity, test design, analysis, validation, and documentation
Work with stakeholders to understand business questions, define requirements, and build scalable data solutions
Continuously improve reporting and analysis workflows by automating or simplifying self-service support for customers

Required Qualifications

3+ years of data engineering experience
1+ years developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes
1+ years developing and operating large-scale data structures for business intelligence analytics using OLAP technologies
1+ years developing and operating large-scale data structures for business intelligence analytics using data modeling
1+ years developing and operating large-scale data structures for business intelligence analytics using SQL
1+ years developing and operating large-scale data structures for business intelligence analytics using Oracle
3+ years of experience in the job offered or a related occupation
1+ years developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform)
Bachelor’s degree (or foreign equivalent) in Computer Science, Engineering, Information Systems, Mathematics, or a related field
Experience with data modeling, warehousing, and building ETL pipelines

Technologies

AWS; EC2; EMR; S3; AWS Glue; Redshift
SQL; Oracle; ETL; ELT; OLAP; data modeling; ETL pipelines
Kinesis; FireHose; Lambda; IAM roles and permissions
Non-relational databases; object storage; document or key-value stores; graph databases; column-family databases

Preferred Qualifications

Experience with AWS technologies including Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
Experience with non-relational databases and data stores, including object storage, document or key-value stores, graph databases, and column-family databases

Benefits

Sign-on payments
Restricted stock units (RSUs)
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

About the Team

The AIGC DIGI Finance team builds and operates scalable data infrastructure and AI solutions for finance and business stakeholders across AIGC. This role works closely with the APM Advertising Finance team, which supports a variety of publishers, including Stores, Amazon Business, Books, Grocery/Physical Store, Devices, Video, and Audio. The team focuses on accelerating top-line revenue and improving profitability by evaluating ad supply monetization and utilization, product feature or sales package adoption, campaign performance, and other product drivers of growth.

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