Job Description
The Accounting BI team supports the global Accounting organization with process automation/improvements, developing automated reporting solutions/tools, and improving the ability of the accounting organization to process, analyze, access and consume accurate and timely financial data. The team supports the global accounting organization and partners closely with all technical roles across the org and various businesses and industries Amazon operates in.
The ideal candidate thrives in a fast-paced environment, relishes working with ambiguity, big data, and enjoys the challenges of highly complex business context. This role requires an individual with a strong data modeling background, deep knowledge of cloud infrastructure, optimizing data for business intelligence solutions, and the ability to quickly learn, adapt and work with a variety of technologies. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and build data sets that answer those questions. You should be able to architect highly efficient data and reporting structures, making a tradeoff between scalability, performance and user functionality needs, using expert knowledge in software development technologies
The ideal candidate thrives in a fast-paced environment, relishes working with ambiguity, big data, and enjoys the challenges of highly complex business context. This role requires an individual with excellent analytical abilities, deep knowledge of business intelligence solutions, and the ability to quickly learn, adapt and work with a variety of technologies.
Key job responsibilities
Working with stakeholders and other engineering teams to identify and scope the right data architecture and technology to be used to facilitate analysis of most common Amazon customer behavioral questions.
Partnering with partner engineering teams to enhance data infrastructure, data availability, and broad access to customer insights made available through BI tools across the organization.
Design, build and implement the right ETL processes using AWS and similar technologies.
Implement anomaly detection systems to have a proactive approach to any potential data quality issues, using industry standard frameworks.
Enable large scale analytics using EMR and other big data technologies
Establishing and implementing technology best practices that should be followed across the organization.
Work on proof of concepts for adoption of new technology and tools
Basic Qualifications
1+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
Experience with SQL
Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
Experience with one or more scripting language (e.g., Python, KornShell)
Knowledge of AWS Infrastructure
Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
Preferred Qualifications
Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
Experience building data pipelines or automated ETL processes
Experience writing and optimizing SQL queries with large-scale, complex datasets
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations
for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
The ideal candidate thrives in a fast-paced environment, relishes working with ambiguity, big data, and enjoys the challenges of highly complex business context. This role requires an individual with a strong data modeling background, deep knowledge of cloud infrastructure, optimizing data for business intelligence solutions, and the ability to quickly learn, adapt and work with a variety of technologies. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and build data sets that answer those questions. You should be able to architect highly efficient data and reporting structures, making a tradeoff between scalability, performance and user functionality needs, using expert knowledge in software development technologies
The ideal candidate thrives in a fast-paced environment, relishes working with ambiguity, big data, and enjoys the challenges of highly complex business context. This role requires an individual with excellent analytical abilities, deep knowledge of business intelligence solutions, and the ability to quickly learn, adapt and work with a variety of technologies.
Key job responsibilities
Working with stakeholders and other engineering teams to identify and scope the right data architecture and technology to be used to facilitate analysis of most common Amazon customer behavioral questions.
Partnering with partner engineering teams to enhance data infrastructure, data availability, and broad access to customer insights made available through BI tools across the organization.
Design, build and implement the right ETL processes using AWS and similar technologies.
Implement anomaly detection systems to have a proactive approach to any potential data quality issues, using industry standard frameworks.
Enable large scale analytics using EMR and other big data technologies
Establishing and implementing technology best practices that should be followed across the organization.
Work on proof of concepts for adoption of new technology and tools
Basic Qualifications
1+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
Experience with SQL
Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
Experience with one or more scripting language (e.g., Python, KornShell)
Knowledge of AWS Infrastructure
Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
Preferred Qualifications
Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
Experience building data pipelines or automated ETL processes
Experience writing and optimizing SQL queries with large-scale, complex datasets
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations
for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Key skill Required
- SQL
- Software Development
- Architecture
- Python
- AWS
- Automation
- Accounting
- Agile methodologies
- Anomaly detection
- Business Intelligence
- Data Architecture
- Data Engineering
- Ambiguity
- Analysis
- Analytics
- Big Data
- Cloud Infrastructure
- Coding Standards
- Communication
- Data Availability
- Data Infrastructure
- Data Modeling
- Data Pipelines
- Data Quality
- Design
- Development
- Facilitate
- Financial Data
- Inclusive
- Infrastructure
- Intelligence
- Management
- New Technology
- Onboarding
- Orientation
- PL/SQL
- Proactive
- Process Automation
- Query Language
- Reporting
- Scalability
- Scripting Language
- Software Engineering
- Source Management
- SPARK
- Writing