Senior Analytics Engineer

PURE InsuranceSan Diego, CA
4d$95,000 - $120,000

About The Position

As a Senior Analytics Engineer, you'll be an important contributor to our data architecture transformation. Your SQL expertise will be the foundation upon which we build our new medallion-style data architecture. You'll be working with cutting-edge tools like Databricks and dbt, turning our data into a powerful, unified ecosystem that drives business decisions.

Requirements

  • Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field
  • Minimum of 3 years of analytics engineering or similar experience, with a strong focus on SQL
  • Proven track record of solving complex data challenges using advanced SQL techniques
  • Ability to communicate technical concepts clearly to both technical and non-technical audiences
  • Experience with cloud-based data warehouses and big data technologies
  • Solid understanding of data modeling concepts and best practices
  • Proficiency in Python or other programming languages used in data analysis

Nice To Haves

  • Experience with dbt, demonstrating ability to quickly adapt to modern data tools
  • Familiarity with Databricks or similar big data platforms
  • Experience with actuarial and pricing data modeling
  • Knowledge of insurance rating systems and pricing tools
  • Knowledge of insurance industry data and regulatory requirements
  • Experience with Preset or similar BI tools, showcasing your end-to-end data skills
  • Understanding of semantic layer implementation and benefits

Responsibilities

  • Contribute to the development of our new medallion-style data architecture in Databricks, applying your analytical expertise to build robust data models
  • Use dbt to help unify and standardize hundreds of regulatory data calls, contributing to the "platinum" layer of our data warehouse and ensuring data consistency across the organization
  • Work with cross-functional teams to understand business needs, translating them into technical solutions that drive decision-making
  • Design and implement data models, ETL processes, and data quality checks, ensuring data integrity and reliability
  • Help optimize data pipelines for performance and scalability, allowing for faster and more efficient data analysis
  • Work with cutting-edge tools such as Databricks, dbt, Hex, and semantic layer technologies, expanding your technical toolkit
  • Share knowledge with team members and promote best practices in data modeling and analysis
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