ADCI HYD
Software Development, Data Engineering, no business category
DataEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Engineer at ADCI HYD. Skills: Data engineering, Data pipelines, AWS technologies. Design data schema. Operate internal data warehouses”
Industry & Context.
Analyze and solve problems at their root; Broader context understanding
What They're Looking For.
Must Have
1+ years of data engineering experience, Experience with data modeling, Experience with warehousing, Experience 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.
Operate internal data warehouses
Operate SQL/NOSQL database systems
Implement data pipelines
Automate data pipelines
Optimize data pipelines
Monitor data pipelines
development and maintenance of metrics
development and maintenance of reports
development and maintenance of analyses
development and maintenance of dashboards
Analyze and solve problems at their root
Step back to understand the broader context
Manage Redshift/SpectrumR infrastructure
Drive architectural plans for future data storage
Drive architectural plans for future reporting
Drive architectural plans for future analytic solutions
Implement architectural plans for future data storage
Implement architectural plans for future reporting
Implement architectural plans for future analytic solutions
Work on different AWS technologies
Explore latest AWS technologies
Learn latest AWS technologies
Provide new capabilities
Work on data lake platform
Work on data lake components
Work on SQL technologies on Hadoop
Recognize best practices in reporting
Recognize best practices in analysis
Adopt best practices in reporting
Adopt best practices in analysis
Conduct rapid prototyping
Conduct proof of concepts
Conceptualize automation tools
Develop automation tools for benchmarking data collection
Develop automation tools for benchmarking analytics
Interface with other technology teams
Extract data from a wide variety of data
Transform data from a wide variety of data
Load data from a wide variety of data
How You'll Work.
Communication Scope
Verbal communication skills; Written communication skills
Full Job Description
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. Data Engineers help us design, manage, and continuously enhance our Analytics needs. You will develop and deliver analytics applications including metrics generation, metrics correlation, modeling, and many other use cases to help improve process effectiveness, customer experience, and automation. As a DE, you will deal with technical aspects of data warehousing (Redshift, Spectrum, EMR, ETL), infrastructure and build data pipelines, tools, and reports that enable program managers, analysts, BIE’s, solution architects, and executives to design and deliver bench marking services for Amazon’s business units. We want to you to feel welcomed, included and valued right from the start. We know that your experiences will help us build a better world Key job responsibilities • Design data schema and operate internal data warehouses and SQL/NOSQL database systems. • Design data models, implement, automate, optimization and monitor data pipelines • Own the design, development and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions • Analyze and solve problems at their root, stepping back to understand the broader context • Manage Redshift/Spectrum/EMR infrastructure, and drive architectural plans and implementation for future data storage, reporting, and analytic solutions • 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 such as Hadoop, Amazon S3 etc. • Work on SQL technologies on Hadoop such as Spark. Hive, Impala etc. • Recognize and adopt best practices in repor
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