Marketing Data Engineer

6 days ago

Sunnyvale, California, United States Fortinet Full time
About the Role

Fortinet is seeking a highly skilled Data Engineer to join our team of Marketing Analysts. The ideal candidate will be responsible for designing and implementing data pipeline architecture, automating and optimizing data flow and collection for cross-functional teams.

Key Responsibilities
  • Data Pipeline Architecture: Design and implement data pipeline architecture to automate and optimize data flow and collection.
  • Data Engineering: Assemble large, complex data sets that meet business requirements, and identify, design, and implement internal process improvements.
  • Infrastructure Development: Build the infrastructure required for optimal extraction, transformation, and loading of data from various data sources using SQL.
  • API Integration: Be comfortable with using 3rd party APIs and extracting data from there and combining it with internal datasets.
  • Analytics Tools: Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
  • Stakeholder Collaboration: Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  • Data Tool Development: Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
Requirements
  • Advanced SQL Knowledge: Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  • Big Data Experience: Experience building and optimizing 'big data' data pipelines, architectures, and data sets.
  • Root Cause Analysis: Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
  • Analytic Skills: Strong analytic skills related to working with unstructured datasets.
  • Project Management: Strong project management and organizational skills.
  • Cross-Functional Team Experience: Experience supporting and working with cross-functional teams in a dynamic environment.
Qualifications
  • Education: A degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.
  • Software/Tools Experience: Experience using relational SQL and NoSQL databases, third-party API use and access, and object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

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