Data Engineer, WWSNA

- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

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Are you ready to elevate your data engineering skills to the next level?
We are seeking a data engineer with deep love for data, who will play a pivotal role in re-architecting our data universe, crafting dynamic pipelines that power our business customers and proper us into the future.

データエンジニアリングのスキルを次のレベルに引き上げる準備はできていますか。
シニアデータエンジニアとして、あなたは私達のデータエコシステムの設計者として活躍し、ビジネスを支えながら未来に進化させることができます。

Key job responsibilities
As a Data Engineer in WWSNA, you will be working in one of the world's largest and most complex data warehouse environments. You will design, implement and support scalable data infrastructure solutions and implement complex data models for Amazon Inbound & Outbound Transportation business. As a DE you will create 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 should have excellent business and communication skills to be able to work with business owners, Product teams and Tech leaders to gather infrastructure requirements, design data infrastructure, build up data pipelines and data-sets to meet business needs. You will be responsible for designing, developing, and operating a data service platform using Python, Airflow, and SQL to build the various ETL, analytics, and data quality components. You’ll automate deployments using AWS CodeDeploy, AWS CodePipeline, AWS Cloud Development Kit (CDK), and AWS Cloud Formation. You will work with AWS services like Redshift, Glue, S3, IAM, CloudWatch, and more.

About the team
S&A (Standardization & Automation) views technology as a true enabler for Finance as data will be available at various grains for analysis and planning. S&A believes that all planning should be automated and driven with business led inputs and automatic calculations to enable comparison of various scenarios. Finance should have the ability to service both the ad-hoc needs of the business (with the speed necessary for business execution) and drive step function changes with technology incorporated into financial processes. In addition, S&A believes that new finance team members should be onboarded with a comprehensive onboarding program that imparts the knowledge and skills needed to execute in their role. S&A improves efficiency for users by delivering time-saving products and providing standardization frameworks to eliminate variance or subjectivity. These efficiencies are measured by hours saved from customers when comparing the old process against S&A’s improvements.