Big Data Engineer

Full Time
Ramat Gan
About us

SeeMetrics resolved the challenge of security metrics consolidation!
SeeMetrics is a security portfolio management platform that consolidates all metric data from across CISO’s organization. SeeMetrics monitors the performance and efficiencies of cyber security products and provides actionable insights for stack optimization. The platform empowers CISO organizations with an independent, easy to use and real-time view into their current cyber operations while unifying all metrics into a single source of truth. Once connected to SeeMetrics, organizations gain a constant view of their security efficiencies, minimizing blind spots, simplifying cumbersome analysis, reducing costs and ultimately improving cyber routine governance.

We are an early stage startup backed up by a US VC.

What will you do?
  • Lead the Big Data topic in the company
  • Design, build, and maintain optimal data pipeline architecture for optimal extraction, transformation, and loading of data from various data sources, including external APIs
  • Design, create and maintain the infrastructure to ingest data into our data lake and data warehouse and provide frameworks and services for operating on that data.
  • Choose the Big Data tools and technologies that will be used
  • Determine the company’s Big Data needs.
  • Consider AI and ML for predictive analytics
  • Be your own DevOps

Requirements
  • At least 6 years of experience as a Data engineer
  • Expertise in large scale development in Python3
  • Experience with Apache Spark/AWS Glue, ElasticSearch, AWS S3 and Serverless architecture
  • Experience in designing and operating data pipeline solutions for a high-volume data flow
  • Track record in designing and building high performant, fault-tolerant, highly available, and secure distributed systems.
  • Proven experience with cloud-based data pipeline and backend services using AWS
  • Experience in Developing and maintaining ETL pipelines from multiple data sources to fuel data applications and business intelligence.
  • Relevant academic background – an advantage
  • Experience working in early stage startup – an advantage
  • Hands-on DevOps experience with AWS - an advantage
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