Data Engineer, Fintech
at Amazon
Posted 7 hours ago
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- Compensation
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Data Engineer on Amazon Finance Tech team to shape the finance data platform across regions, designing scalable data models and secure access to large datasets using AWS. Build and maintain ETL pipelines, dashboards, and metrics for reporting to drive business decisions. Collaborate with finance analysts and stakeholders to implement best practices for data integrity and self-service reporting, while continually scaling the data architecture to handle growing volumes.
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 AWS services. 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.
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