Data Engineer (Python/AWS)

As a Data Engineer, you will be working on building and maintaining complex data pipelines, assembling large and complex datasets to generate business insights and enable data-driven decision making in a rapidly growing, dynamic environment.

You will have an opportunity to collaborate with Business Analysts, Managers, Software Development Engineers, and Data Engineers to determine how best to design, implement and support solutions. This role offers growth opportunities in a customer-facing, fast-paced, agile environment.

Design, implement and support analytical data platform solutions for data-driven decisions and insights

Design data schemas and operate internal data warehouses & SQL/NOSQL database systems

Work on different data model designs, architecture, implementation, discussions and optimizations

Interface with other teams to extract, transform, and load data from a wide variety of data sources using AWS big data technologies like EMR, RedShift, Elastic Search

Work with AWS technologies such as S3, RedShift, Lambda, Glue, etc., and explore the latest AWS technologies to provide new capabilities and increase efficiency

Work on data lake platform and components in the data lake such as Hadoop and Amazon S3

Work on SQL technologies on Hadoop such as Spark, Hive, and Impala

Help continually improve ongoing analysis processes, optimizing or simplifying self-service support for customers

Demonstrate strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment

Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation

Collaborate closely with peers in a team of talented engineers to gain knowledge

Own the development and maintenance of ongoing metrics, reports, analyses, dashboards, etc. 1+ years of data engineering experience

• Experience with data modeling, warehousing and building ETL pipelines
• Experience writing and optimizing SQL queries with large-scale, complex datasets
• Experience with one or more scripting languages (e.g., Python, KornShell)
• Experience with big data processing technology (e.g., Hadoop or Apache Spark), data warehouse technical architecture, infrastructure components, ETL, and reporting/analytic tools and environments

Experience with ETL tools such as Informatica, ODI, SSIS, BODI, Datastage, etc.

Proficiency in dbt, Airflow/MWAA, AWS Glue, Kinesis

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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