Data Engineer III

O projekcie:
**Our compensation structure is the base salary and equity in the form of restricted stock units.

WHAT IS BOX?

Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. We help companies thrive in the new AI-first era of business. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia.

By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift.

WHY BOX NEEDS YOU

Data Engineering initiative inside box is expanding and this role will help build the data platform engineering features and capabilities of the cloud cost management platform.

In this role you will be working alongside our team building data pipelines, support our product and analytics team members, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.

Wymagania:
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3+ Years of relevant industry or relevant academia experience working with large amounts of data



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Experience building and optimizing scalable data pipelines, architectures and data sets


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Be cognizant of emerging technology trends and find adoption opportunities to improve existing development processes


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Expert in SQL


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Experience with at least one of the programming languages: Scala, Java


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Experience with scripting language: Python, NodeJS


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Experience with GCP (BigQuery, Dataproc, Dataflow/Fusion)


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Experience with big data tools: Hadoop, Spark, Kafka, etc


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Strong analytic skills related to working with structured and unstructured datasets


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Experience supporting and working with cross-functional teams in a dynamic environment


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Familiarity with Virtualization/container abstractions and orchestration (Kubernetes, Docker, etc.)


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Familiarity with Visualization software: Tableau


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Familiarity with frontend web framework: React

Codzienne zadania:
- Work with a team of high-performing data engineers and analysts to identify business opportunities, design and build scalable data solutions
- Build and own data pipelines that clean, transform, and aggregate data from disparate sources
- Create and maintain optimal data pipeline architecture
- Assemble large, complex data sets that meet functional / non-functional business requirements
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using GCP BigQuery and Spark
- Build analytics tools that utilize the data pipeline to provide actionable insights into operational efficiency and other key business performance metrics
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader
- Influence across teams and other functions, build best practices across the organization