Data Engineer, Fintech

Does the prospect of dealing with massive volumes of data excite you? Do you want to lead scalable data engineering solutions using AWS technologies? Do you want to create the next-generation tools for intuitive data access? Amazon’s Finance Tech team needs a Data Engineer to shape the future of the Amazon finance data platform by working with stakeholders in North America, Asia and Europe. The team is committed to building the next generation big data platform that will be one of the world’s largest finance data warehouses by volume to support Amazon’s rapidly growing and dynamic businesses, and use it to deliver the BI applications which will have an immediate influence on day-to-day decision making. Members of the team will be challenged to innovate using the latest big data techniques. We are looking for a passionate data engineer to develop a robust, scalable data model and optimize the consumption of data sources required to ensure accurate and timely reporting for the Amazon businesses. You will share in the ownership of the technical vision and direction for advanced reporting and insight products. You will work with top-notch technical professionals developing complex systems at scale and with a focus on sustained operational excellence. We are looking for people who are motivated by thinking big, moving fast, and exploring business insights. If you love to implement solutions to hard problems while working hard, having fun, and making history, this may be the opportunity for you.

Key job responsibilities
Design, implement, and support a platform providing secured access to large datasets. Interface with tax, finance and accounting customers, gathering requirements and delivering complete BI solutions. Collaborate with Finance Analysts to recognize and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation. Model data and metadata to support ad-hoc and pre-built reporting. Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions. Tune application and query performance using profiling tools and SQL. Analyze and solve problems at their root, stepping back to understand the broader context. Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use. Keep up to date with advances in big data technologies and run pilots to design the data architecture to scale with the increased data volume using AWS. Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for datasets. Triage many possible courses of action in a high-ambiguity environment, making use of both quantitative analysis and business judgment.

Basic Qualifications

– 1+ years of data engineering experience
– Experience with SQL
– 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)

Preferred Qualifications

– Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
– Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.