Скачать или смотреть Big Data Engineer interview questions and answers

A big data engineer is an information technology (IT) professional who is responsible for designing, building, testing and maintaining complex data processing systems that work with large data sets. This type of data specialist aggregates, cleanses, transforms and enriches different forms of data so that downstream data consumers -- such as business analysts and data scientists -- can systematically extract information.

What is big data?
Big data is a label that describes massive volumes of customer, product and operational data, typically in the terabyte and petabyte ranges. Big data analytics can be used to optimize key business and operational use cases, mitigate compliance and regulatory risks and create net-new revenue streams.

Data sources include:

credit card and point-of-sales transactions;
e-commerce transactions;
social media engagements;
smartphone and mobile device engagements; and
sensor readings generated by the internet of things (IoT).
Insights that can be gained by big data include:

optimizing key business and operational use cases;
mitigating compliance and regulatory risks;
creating net-new revenue streams; and
building compelling, differentiated customer experiences.
What is the role of a big data engineer?
It is the role of a big data engineer to build, maintain and ensure a production-ready big data environment. This environment this role works in will include architecture, technology standards, open source options, as well as data preparation and data management processes. The big data engineer's role is to:

Design, construct and maintain large-scale data processing systems. This collects data from various data sources -- structured or not.
Store data in a data warehouse or data lake repository.
Handle raw data using data processing transformations and algorithms to create predefined data structures. Deposit the results into a data warehouse or data lake for downstream processing.
Transform and integrate various data into a scalable data repository (such as a data warehouse, data lake, cloud).
Understand different data transformation tools, techniques and algorithms.
Implement technical processes and business logic to transform collected data into meaningful and valuable information. This data should meet the necessary quality, governance and compliance considerations for operational and business usage to be considered trustable.
Understand operational and management options, as well as the differences between data repository structures, massively parallel processing (MPP) databases and hybrid cloud
Evaluate, compare and improve data pipelines. This includes design pattern innovation, data lifecycle design, data ontology alignment, annotated data sets and elastic search approaches.
Prepare automated data pipelines to transform and feed the data into dev, QA and production environments.
What are big data engineer skills and responsibilities?
Big data engineers gather, prepare and ingest an organization's data into a big data environment. They prepare and create the data extraction processes and data pipelines that automate data from a wide variety of internal and public source systems. Big data engineers also create the algorithms that transform the data into an operational or business format.


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