Data Engineer, RACE Anaplan Team

Amazon Web Services (AWS), World-Wide Public Sector Reporting and Analytics team is seeking a Data Engineer with broad technical skills to help build the infrastructure and tools required to support our Anaplan Forecasting and Planning tools team.

In this role, the ideal candidate will be responsible for developing and managing big data systems using advanced data engineering knowledge in the data warehousing space and redefining best practices with a cloud-based approach to scalability and automation. Additionally, you will be responsible for scaling our existing infrastructure, incorporating new data sources, and building robust data pipelines for production level systems. In partnership with machine learning engineers, business intelligence engineers and analysts, you will work backwards from our business questions to build reliable and scalable data solutions to meet the business needs. Finally, this individual will work closely with project management teams to ensure proper guidance, use cases, and documentation is available to our Sales and Operations teams.

Responsibilities include:
- Partnering with the Anaplan dev team and owning the data pipelines going into and out of the planning tools
- Understand existing databases and warehouse structures in order best determine how to consolidate and aggregate data in an efficient and scalable way.
- Design and code all aspects of data solutions using Amazon Redshift (SQL Server) to build out an Operations data warehouse.
- Create and propose technical design documentation, which includes current and future ETL functionality, database objects affected, specifications, and flows and diagrams to detail the proposed implementation.
- Design, develop, implement, test, document, and operate large-scale, high-volume, high-performance data structures for business intelligence analytics.
- Implementing data structures using best practices in data modeling to provide on-line reporting and analysis using business intelligence tools and a logical abstraction layer against large, multi-dimensional datasets and multiple sources.
- Evaluating and making decisions around dataset implementations designed and proposed by peer data engineers. Mentor junior data engineers.
- Manage AWS resources including EC2, Redshift, S3, etc. Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency.
- Participating in the full development life cycle, end-to-end, from design, implementation and testing, to documentation, delivery, support, and maintenance to produce comprehensive, usable dataset documentation and metadata.

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