ADCI HYD 13 SEZ
E-Commerce
BigDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Big Data Engineer at ADCI HYD 13 SEZ. Skills: Data engineering, Data pipelines, Data warehousing. Build data architectures. Build data platforms”
Industry & Context.
What They're Looking For.
Must Have
1+ years of data engineering experience, Experience with SQL, Experience with data modeling, Experience with warehousing, Experience building ETL pipelines, Experience with SQL, Experience with PL/SQL, Experience with DDL, Experience with MDX, Experience with HiveQL, Experience with SparkSQL, Experience with Scala, Experience with Python, Experience with KornShell
Nice to Have
Experience with Hadoop, Experience with Hive, Experience with Spark, Experience with EMR, Experience with Informatica, Experience with ODI, Experience with SSIS, Experience with BODI, Experience with Datastage
What You'll Do.
Build data architectures
Design data pipelines
Develop data pipelines
Operate data pipelines
Recognize best practices
Evaluate software products
Make decisions on software
Design data architecture
Build data warehouse components
Own data warehouse components
Provide data engineering support
Improve reporting processes
Improve analysis processes
Automate self-service support
Simplify self-service support
Interface with technology teams
Own software system scaling
Implement big data solutions
Lead data pipeline launch
Drive database design
Spearhead best practices
How You'll Work.
Team & Collaboration
Product managers; Program managers; Engineering leaders; Business leaders; Technology teams
Full Job Description
Profit Intelligence team in Amazon Retail is seeking a seasoned and talented Senior Data Engineer to join the Historical Contribution Profit (HCP) team. HCP is a fast growing team with a mandate to build tools to automate profit-and-loss forecasting and planning for the Physical Consumer business. We are building the next generation data and Business Intelligence solutions using big data technologies and native AWS (NAWS). As a Data Engineer in Amazon, you will be working in a large, extremely complex and dynamic data environment. You should be passionate about working with big data and are able to learn new technologies rapidly and evaluate them critically. You should have excellent communication skills and be able to work with business owners to translate business requirements into system solutions. You are a self-starter, comfortable with ambiguity, and working in a fast-paced and ever-changing environment. Ideally, you are also experienced with at least one of the programming languages such as Java, Spark/Scala, Python, etc. Major Responsibilities: - Work with a team of product and program managers, engineering leaders, and business leaders to build data architectures and platforms to support business - Design, develop, and operate high-scalable, high-performance, low-cost, and accurate data pipelines in distributed data processing platforms - Recognize and adopt best practices in data processing, reporting, and analysis: data integrity, test design, analysis, validation, and documentation - Keep up to date with big data technologies, evaluate and make decisions around the use of new or existing software products to design the data architecture - Design, build and own all the components of a high-volume data warehouse end to end. - Provide end-to-end data engineering support for project lifecycle execution (design, execution and risk assessment) - Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for cus
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