Data Engineering Manager, WW Ops Finance S&A

- 2+ years of processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution) experience
- 2+ years of relational database technology (such as Redshift, Oracle, MySQL or MS SQL) experience
- 2+ years of developing and operating large-scale data structures for business intelligence analytics (using ETL/ELT processes) experience
- 5+ years of data engineering experience
- Experience managing a data or BI team
- Experience communicating to senior management and customers verbally and in writing
- Experience leading and influencing the data or BI strategy of your team or organization
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with AWS Tools and Technologies (Redshift, S3, EC2)

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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 Engineering Manager to lead the establishment of 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 Engineering Manager in WWSNA, you will be responsible for managing one of the world's largest and most complex data warehouse environments, all while navigating a high level of ambiguity. Your role will involve designing, implementing, and supporting scalable data infrastructure solutions, as well as implementing complex data models for Amazon Inbound & Outbound Transportation business. You should have excellent business and communication skills to collaborate with business owners, Product teams, and Tech leaders to gather infrastructure requirements, design data infrastructure, and build data pipelines and datasets to meet business needs. Your responsibilities will include designing and delivering a data service platform using Python, Airflow, and SQL to build various ETL, analytics, and data quality components. You'll also be in charge of automating deployments using AWS CodeDeploy, AWS CodePipeline, AWS Cloud Development Kit (CDK), and AWS CloudFormation. In addition, you will work closely with AWS services like Redshift, Glue, S3, IAM, CloudWatch, and more to ensure the success of data engineering initiatives.

Key job responsibilities
As a Data Engineering Manager, you will lead a team of engineers solving problems for Finance customers. Your role will entail serving as the team's Solution Architect, guaranteeing the delivery of solutions at the utmost level of quality and standards. You should be an expert in the architecture of DW solutions for the Enterprise using multiple platforms. You should excel in the design, creation, management, and business use of extremely large data sets. You should have excellent business and communication skills to be able to work with business analysts and engineers to determine how best to design the data warehouse for reporting, analytics and science projects. You will be responsible for leading designs and deliver scalable ETL processes in the data lake platform to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as service which will have an immediate influence on day-to-day decision making.