Data Engineer


Job Overview

Amazon Web Services (AWS) provides companies of all sizes with an infrastructure web services platform in the cloud (“cloud computing”). With AWS, you can procure compute power, storage, and many other services – gaining access to a suite of elastic IT infrastructure services as your business demands them. AWS is the leading platform for designing and developing applications for the cloud and is growing rapidly with hundreds of thousands of companies in over 190 countries on the platform.As a Data engineer with AWS Americas Sales Insights , Analytics & Data Science team , you will be working in a large, complex, and dynamic data environment. We are looking for an experienced Data Engineer with an uncanny ability to integrate multiple heterogeneous data sources to build efficient, flexible, and scalable data warehouse and reporting solutions. The ideal candidate has deployed analytics platforms to 5000+ users, optimizing the architecture for performance and positive end-user experience. You are enthusiastic about learning new technologies and implementing solutions using these technologies to empower internal customers and scale the platform. You demonstrate solid communication skills and the ability to partner with Research Scientists and business owners across technical and non-technical teams to develop and define key business questions, then build the solutions that answer those questions.In this role, you your will pioneer a self-service feature repository serving multiple stakeholders. Data pipelines will originate from AWS-based infrastructure and require familiarity with tools such as Redshift, Kinesis, Secret Manager, Glue ETL, Spectrum, and Athena. You will own the global data model and be responsible for incrementally advancing it as a single source of truth for statistical models, distributed systems, and individual users. You will maintain “operational excellence utilities” and advise on feature enhancements.will serve as the expert in designing, implementing, and operating a stable, scalable, low cost environment to flow information from the data warehouse into end-user facing reporting applications such as Tableau or AWS QuickSight. Above all, you will bring large datasets together to answer business questions and drive data-driven decision making.Key responsibilities include:· Create ETL procedures and SQL queries to bring data in from data warehouse and alternate data sources· Establish scalable, efficient, automated processes for large scale data analyses· Support the development of performance dashboards & data sets that will generate the right insight. Work with business owners and partners to build data sets that answer their specific business questions.· Support Sales Operations Leads, Business Analysts and Data Scientists in analyzing usage data to derive new insights and fuel customer successAmazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.Basic qualificationsBasic Qualifications· Bachelor degree in Computer Science or related technical field .· 3+ years of experience working on ETL, data modeling, business intelligence architecture. Experience with SQL to query relevant datasets· Experience building self-service reporting solutions using business intelligence software (e.g., OBIEE, Tableau, Amazon Quicksight, etc.)· Ability to complete projects timely, accurately and with strong attention to detail, with continuous communication of progress updates to stakeholdersPreferred qualification Preferred Qualifications· Experience with Amazon Redshift, QuickSight, S3· Experience with scripting languages like Python, Ruby, or Unix shell scripts· Experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with large-scale, complex datasets· Experience with Tableau, QuickSight, OBIEE or similar BI Reporting Platform· Data visualization and dashboarding experience· Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation, and model implementation· Develop solutions that utilize the highest standards of analytical rigor and data integrity· Exceptional troubleshooting and problem-solving abilities· Excellent verbal/written communication & data presentation skills, including experience communicating to both business and technical teams· Demonstrated ability to work effectively across various internal organizations

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