Job
Description
Are you passionate about building business insights that drive decision making at the highest levelsDo you want to be a part of a fast-paced, ambiguous environment and contribute to Amazon Translation Services In this role you will be responsible for solving complex and ambiguous data and metric problems. You will use latest AWS provided Data Analytics and GenAI tools (such as Quick-sight, Amazon Q) to provide business metrics for TS org customers and stakeholders. You should have a track record of end-to-end ownership and successfully delivering results in a fast-paced and dynamic business environment. You should be able to work on complex initiatives, deal with ambiguity. You will be required to work with senior leaders, data engineers, data scientist, SDEs, operations, program managers and other data teams As a business intelligence engineer, you will/may: Be highly data driven, resourceful, customer-obsessed and team oriented Use latest AWS provided data analytics and tools such as Quicksight, Amazon Q, Redshift, Glue etc Design, develop, and implement scalable, automated processes for data extraction, processing, and evaluation Define data driven approaches and metrics strategy to uncover new insights Have a passion for sourcing, manipulating, and visualizing data to tell business stories Be able to clearly communicate strategic findings and recommendations Translate complex, technical concepts into business terms and vice versa Work with engineering and data teams to support the development of tools and dashboards - 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience - Experience with data visualization using Tableau, Quicksight, or similar tools - Experience with data modeling, warehousing and building ETL pipelines - Experience in Statistical Analysis packages such as R, SAS and Matlab - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling - Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift - Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
