Data Engineer, Financial Close Systems

Job summary
Are you interested in building high-performance, globally scalable Financial systems and infrastructure that support Amazon's current and future growth? Are you seeking an environment where you can drive innovation? Does the prospect of working with top finance and engineering talent get you charged up? If so, Amazon Finance Technology (FinTech) is for you!

We are seeking an outstanding Data Engineer to join our team. Amazon has a culture of data-driven decision-making and demands business intelligence that is timely, accurate, and actionable.

As a Data Engineer, you will be solving data related problems in Accounting and Finance domain. You will design, implement and support scalable data infrastructure solutions to integrate with multi heterogeneous data sources, aggregate and retrieve data in a fast and safe mode, curate data that can be used in reporting, analysis, machine learning models and ad-hoc data requests. You will be exposed to cutting edge AWS big data technologies. You should have excellent business and communication skills to be able to work with business owners and Tech leaders to gather infrastructure requirements, design data infrastructure, build up data pipelines and data-sets to meet business needs. You stay abreast of emerging technologies, investigating and implementing where appropriate.





Key job responsibilities
In the role, you will work closely with product managers, scientists and software engineers to build out infrastructure, data pipelines, and reporting mechanisms for our team.

Our Data Engineer duties & responsibilities will include:

Design and deliver end-to-end automation of data pipelines, making datasets readily-consumable by downstream systems and visualization tools.
Create automated alarming and dashboards to monitor data integrity.
Create and manage capacity and performance plans.
Act as the subject matter expert for the data structure and usage.

About the team
FinTech’s charter is to enable Finance & Global Business Services (FGBS) teams, and amplify the benefit of FGBS teams to support the growth, expansion, and restructuring of the businesses. The Close Systems team owns coordination, execution and continuous improvement for month close processes across FGBS teams. We own developing automation to scale with Amazon’s growth, reduce manual effort and defects, streamline processes, and drive accountability across teams. The Close Systems team improves the financial close by developing automation to scale with Amazon’s growth, reduce manual effort and defects, streamline processes, and drive accountability across teams.

Basic Qualifications

• 3+ years of experience as a Data Engineer or in a similar role
• Experience with data modeling, data warehousing, and building ETL pipelines
• Experience in SQL

Excel in the design, creation, and management of very large datasets.
Detailed knowledge of cloud-based data warehouses, architecture, infrastructure components, ETL and reporting/analytic tools and environments.
Skilled with writing, tuning, and troubleshooting SQL queries
Experience with Big Data technologies such as Hive/Spark, AWS EMR, AWS Glue, AWS Lambda , Kinesis, Redshift, Lake Formation.
Proficiency in one of the languages - PL/SQL, python, ruby, java or similar.
Excellent understanding of software development life cycle and/or agile development environment with emphasis on BI practices.
Strong organizational skills and planning prowess, with excellent attention to detail.

Preferred Qualifications

· Hands-on experience and advanced knowledge of Python etc.
· Strong experience in distributed data Data and Data Warehousing
· Masters in mathematics, statistics, economics, or other quantitative fields.
· 5+ years of experience as a Data Engineer, BI Engineer or related field in a company with large, complex data sources.
· Experience working with AWS big data technologies
· Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
· Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy.
· Familiarity with solving data quality issues and auto detection algorithms
· Meets/exceeds Amazon’s leadership principles requirements for this role
· Meets/exceeds Amazon’s functional/technical depth and complexity for this role
# Security Assurance



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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.