Data Engineer- Analytics Expert

Job Overview
Be responsible for expanding and optimizing data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. Senior software engineer will instruct our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.
Responsibilities
● Create and maintain optimal data pipeline architecture,
● Assemble large, complex data sets that meet functional / non-functional business requirements.
● Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
● Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS or Azure ‘big data’ technologies.
● Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
● Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
● Keep our data separated and secure across national boundaries through multiple data centers and AWS or Azure regions.
● Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
● Work with data and analytics experts to strive for greater functionality in our data systems.








































































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