Data Engineer, WW Standardization & Automation(WWSnA)
DESCRIPTION
Are you passionate about standardizing data platforms and automating data engineering to drive analytics and reporting? Do you excel in dynamic, fast-paced environments and find joy in converting data into actionable insights? Are you adept at implementing data governance practices and defining data access and quality standards? If you thrive in innovation and can deliver scalable Data Engineering Solutions, then the Worldwide Operations Finance Standardization & Automation (SnA) team has an exciting opportunity for you! We are seeking a customer-centric Data Engineer to establish a reliable and accessible data platform, ensuring Operations Finance customers have complete trust in the data, technology, and tools to make data-driven business decisions.
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 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.
Key job responsibilities
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using Python, SQL and AWS big data technologies.
- Designing and implementing complex pipelines and other Data Engineering solutions.
- Work closely with Senior Data Engineers, Product Managers and BI Engineers to explore new data sources and deliver the data.
- Create new solutions as required based on team and stakeholder needs
BASIC QUALIFICATIONS
- 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)
- Bachelor's degree
- Knowledge of distributed systems as it pertains to data storage and computing
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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