Data Engineer

Industry: Insurance
Remote
Company size: 51-250
Full-time
Not disclosed

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Job description

A US-based company that is utilizing AI and Machine Learning technologies to accelerate commercial insurance performance is looking for a Data Engineer. The engineer will be taking ownership of the current data for product insights to create a roadmap for future development. The company's advanced technology is enabling businesses to unlock the value in their unstructured data. The company has managed to successfully raise $30mn+ during their Series C round of funding. 

 

Job Responsibilities:

  • Assist in the design and implementation of the company’s data platform from the ground up
  • Conduct tooling and integrations for data ingestion, Kappa or Lambda architectures for stream and batch processing, monitoring, etc. 
  • Build end-to-end ETL/LT pipelines to populate the Data Warehouse 
  • Collaborate with Product, Engineering, Data Science, Analytics/BI, and Operations team to understand their data requirements and engineer solutions accordingly 
  • Act as a technical leader and mentor junior engineers on the team

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 3+ years of relevant experience as a data engineer
  • At least 3+ years of experience working with one or more programming languages like Scala and Python/PySpak
  • Extensive experience working with SQL databases
  • A minimum of 3+ years of experience developing data platform infrastructure 
  • Demonstrable background working with distributed big data technologies such as Spark, Presto, Hive, Redshift, etc.
  • Prolific experience with schema design, dimensional data modeling, and large-scale data warehousing architecture
  • Expertise in designing, implementing, and maintaining data pipelines through efficient ETL design, implementation, and maintenance
  • Prior experience providing technical leadership and mentoring other engineers for best practices in the data engineering space
  • Solid knowledge of agile software development and continuous integration/deployment principles
  • Fluent in verbal and written English

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