ADCI
Finance
DataEngineer,,GFS(GlobalFinanceSolution)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Engineer, , GFS (Global Finance Solution) at ADCI. Skills: Data engineering, Data pipelines, AWS technologies, SQL. Design analytical data platform solutions. Design data schema”
What You'll Achieve.
Generate business insights; Enable data driven decision making; Support business demand for data; Drive key business decisions
Industry & Context.
Data driven decision making
What They're Looking For.
Must Have
1+ years of data engineering experience, Experience with SQL, Experience with data modeling, Experience with building ETL pipelines, Experience with one or more query language, Experience with one or more scripting language
Nice to Have
Experience with big data technologies, Experience with any ETL tool
What You'll Do.
Design analytical data platform solutions
Operate internal data warehouses
Operate SQL database systems
Operate NOSQL database systems
Work on different data model designs
Work on data architecture
Work on data implementation
Work on data optimizations
Extract data from data sources
Transform data from data sources
Load data from data sources
Explore AWS technologies
Learn AWS technologies
Work on data lake platform
Work on data lake components
Work on SQL technologies on Hadoop
Improve analysis processes
Optimize analysis processes
Simplify self-service support
Recognize best practices in reporting
Recognize best practices in analysis
Adopt best practices in reporting
Adopt best practices in analysis
Build domain knowledge
Own development of metrics
Own maintenance of metrics
Own development of reports
Own maintenance of reports
Own development of analyses
Own maintenance of analyses
Own development of dashboards
Own maintenance of dashboards
How You'll Work.
Team & Collaboration
Collaborate with Business analysts; Collaborate with Managers; Collaborate with Business Intelligence; Collaborate with Data Engineers; Work closely with peers
Communication Scope
Verbal communication skills; Written communication skills
Full Job Description
About the Organization: Amazon is a US-based multinational electronic commerce company headquartered in Seattle, Washington. Amazon.com started as an online bookstore, but soon diversified into many other categories, with a vision to be earth's most customer-centric company & to build a place where people can come to find and discover anything they might want to buy online. About the role: Amazon's Global Finance Services (GFS) team is a fast-paced, team-focused, dynamic environment and delivering great experiences for our customers is top priority. GFS is seeking a Business Intelligence Engineer to support our Amazon Music finance team. As a Data Engineer, You will be working on building and maintaining complex data pipelines, assemble large and complex datasets to generate business insights and to enable data driven decision making and support the rapidly growing and dynamic business demand for data. You will have an opportunity to collaborate and work with various teams of Business analysts, Managers, Business Intelligence, and Data Engineers to determine how best to design, implement and support solutions. You will be challenged and provided with tremendous growth opportunity in a customer facing, fast paced, agile environment. Key job responsibilities * Design, implement and support an analytical data platform solutions for data driven decisions and insights * Design data schema and operate internal data warehouses & SQL/NOSQL database systems * Work on different data model designs, architecture, implementation, discussions and optimizations * Interface with other teams to extract, transform, and load data from a wide variety of data sources using AWS big data technologies like EMR, RedShift, Elastic Search etc. * Work on different AWS technologies such as S3, RedShift, Lambda, Glue, etc.. and Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency * Work on data lake platform and different components in the data lake s
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