BI (Analytics) Engineer

San Francisco, United StatesOn-site

Requirements

This role will improve and scale our data infrastructure, enabling future ML and AI products - Implement New Processes and Systems for Data Collection and Analysis: Deep dive with engineers to understand complex production data.
Ensure that tooling and visualization platforms are accurate and available WHO YOU ARE - You have Bachelors degree in Math, Science, Engineering, or another data intensive field of study such as Library Science - You have 4+ years of
experience working in a Data Science, Data Analytics, or Data Engineering at a high growth startup or scaled technical organization - You have
experience working with data models, data pipelines and performing analysis - You have hands on
experience working with common data warehouses such as Snowflake, BigQuery, or Redshift - Enthusiasm for data modeling; hopefully you have opinions on slow changing dimensions - You have a strong understanding of SQL and have used it in complex data environments - You have well-developed opinions on modern data engineering and an ability to bring others up to speed - You thrive in ambiguity and enjoy tackling complex tasks that have significant impact on the business at large - You’re a clear and concise -
Experience or exposure with the broader set of technologies in our ecosystem: Google Cloud Platform (BigQuery), Metabase, Terraform, Python, DBT.

PAY TRANSPARENCY The estimated starting annual salary range for this position is $135,000 to $180,000 USD.
The listed range is a guideline from Pave https://www.pave.com/ data, and the actual base salary may be modified based on factors including job-related skills, experience/qualifications, interview performance, market data, etc. Total compensation for this position may also include equity, sales incentives (for sales roles), and employee benefits.
Given Candid Health’s funding and size, we heavily value the potential upside from equity in our compensation package.

THE ROLE At Candid Health, we’re searching for an Analytics Engineer to bridge Analytics Engineering, Business Intelligence, and Data Analysis.