Data Engineer, AWS Fintech

- Bachelor's degree
- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- 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, Scala)
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $91,200/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Do you want to build a cutting-edge highly scalable data platform using Amazon Web Services (AWS) technologies? How about building this platform to support the fast growth of AWS itself? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Web Services.

AWS Fintech is seeking a Data Engineer (DE) with a passion for developing data architecture and tools to support self-service data analytics. You will play a critical role supporting AWS Finance BI and building solutions to support data needs in one of the world's largest and most complex data environments. In this role, you will have ownership of end-to-end development of data engineering solutions to complex questions and you’ll play an integral role in strategic decision-making.

The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and the ability to work in a fast-paced environment. You will build and manage analytical resources on AWS and support content-related projects. You should have deep expertise in the design, creation, management, and business use of extremely large datasets. Above all you should be passionate about working with huge data sets and eager to learn new solutions to answer business questions and drive change.

Key job responsibilities
In this role, you will have the opportunity to display and develop your skills in the following areas:
- Design, implement, and support an analytical platform providing ad hoc access to large datasets and computing power
- Managing AWS resources including EC2, RDS, Redshift, Lambda, and etc.
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies
- Build robust and scalable data integration (ETL) pipelines using SQL, Python and Spark.
- Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
- Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.

A day in the life
- Working closely with BI engineers, software developers, product managers and other business stakeholders to solve unique business problems.
- Leverage new cloud architecture and data engineering patterns to ingest, transform and store data.
- Build and deliver high quality data solutions to support analysts, engineers and data scientists.