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Data Pipeline Optimization Expert

hace 2 semanas

San José, San José, Costa Rica Infutor A tiempo completo

About Our Company

We are a rapidly-growing company that specializes in data, technology, and analytics. Our mission is to provide advanced decision-support to prevent credit, lending, and cyber risks.

Our team uses AI, machine learning, automation, and other emerging technologies to collect and analyze billions of records. We monitor and advise companies on complex global matters such as climate change, catastrophes, and geopolitical issues.

As a Data Engineer, you will play a key role in expanding and optimizing our data pipeline architecture. You will work closely with our product delivery, engineering, analytics, and data science teams to ensure optimal data delivery architecture is consistent throughout ongoing projects.

Key Responsibilities:

  • Help architect and maintain our code base for ETL pipelines, large batch processing, and streaming systems
  • Assemble large, complex data sets that meet functional / non-functional business requirements
  • Create and maintain toolsets to help manage our enterprise data pipelines
  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Ensure our code meets quality standards and architectural requirements
  • Help build out the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS 'big data' technologies
  • Comfortable writing stories and associated acceptance criteria for agile/scrum workflow
  • Help keep our data separated and secure across multiple data centers and AWS regions

Requirements:

  • Experience working under agile/scrum and the major pieces of that framework (epics, stories, sprint planning and retros)
  • Intermediate/Advanced knowledge of Python
  • Experience with and knowledge of large batch data processing
  • Experience with SQL and NoSQL databases, and an understanding of key concepts (Foreign Keys, Indices, etc)
  • Experience with Big Data technologies, preferably PySpark/ Spark, Airflow, or Pandas
  • Experience seeing the full end to end SDLC of a system to production
  • Basic understanding of bash scripting, and the basics of Linux operating systems
  • Understanding of Microservice architecture and preferably familiarity with 12 Factor architecture
  • Experience with CI/CD, such as Jenkins + Gitlab
  • 1-2 years experience developing and deploying solutions on AWS and familiarity with AWS' ecosystem of services
  • Experience with Docker or Kubernetes a plus
  • Experience with stream-processing systems a plus
  • Experience with BDD/TDD is a plus