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Analytics Engineer

Kin Insurance LogoKin Insurance
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As an Analytics Engineer, you will develop cutting-edge data infrastructure to create highly scalable analytical resources and be a critical part of the growth and expansion of Kin Insurance. As the Analytics Engineer, you will design and build innovative data and analytics solutions on AWS, using core data warehousing tools, cloud data warehouses, and other big data-related technologies (Redshift, Airflow, Jupyter, Lambda, Glue, DBT). In addition, you will be working with some of the most forward-thinking departments in data, analytics, and engineering across the organization.

A day in the life could include:

  • Model data and metadata to support commercial, insurance, and data science analysis
  • Create and implement custom data solutions to solve for complex business problems
  • Design and build data extraction, transformation, and loading processes by writing custom data pipelines with Python
  • Be a key member of a highly collaborative agile team that works with business stakeholders to understand data needs, capture requirements, and deliver complete Business Intelligence solutions
  • Aid in communication across the technical teams at Kin, filling in knowledge gaps where needed
  • Build data expertise and own data quality for allocated areas in key departments supporting Marketing, Insurance Product and Underwriting
  • Work with data infrastructure to triage ETL issues and drive resolutions
  • Develop custom applications to streamline procedures that do not fit in the existing technical infrastructure

I’ve got the skills… but do I have the necessary ones?

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline
  • 3+ years of experience developing ETL workflows with SQL, working with Redshift and/or Postgres
  • 2+ years of technical experience using BI tools such as Looker or Tableau, and data warehousing tools such as Azure, Snowflake, Redshift, SQL server and/or DBT.
  • Proficient in Python and SQL
  • Ability to create and optimize complex data processing and data transformation pipelines using Python and SQL in a work environment setting is a must
  • Proven working knowledge of establishing, presenting and utilizing data analytics standard methodologies in a BI environment

Bonus Points:

  • Insurance background a plus
  • Experience using Looker
  • Interest in broader insurtech data science and machine learning
  • AWS, Redshift, and/or DBT experience
  • Command line skills for collaborative project management
  • GUI, dash, and/or flask app development experience

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