BI (Analytics) Engineer
Candid Health · On-site
MeritLog read this listing from Candid Health's Ashby job board and last checked it on September 10, 2026.
Source: the employer's Ashby job board. Open the original listing for current details.
Job details
- Work model
- On-site
- Salary
- $135,000 – $180,000 per year
- Location
- San Francisco
Hiring context
How this role compares at Candid Health
Candid Health has 38 live roles in MeritLog’s catalog across 10 job families, and 10 of them are in data & analytics. 28 of those listings publish a pay range, a disclosure rate of 74%.
This role's posted range of $135,000 – $180,000 per year sits above 24% of the 25 other Candid Health roles quoted over the same currency and period.
Candid Health concentrates this hiring in:
Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.
What the role asks for
What you'd do
- Own Data Modeling as a Practice: Build and deliver critical reporting, analytics, and data models for varying use cases. You will be the standardbearer for operational excellence in our efforts to extrapolate data for meaningful outcomes
- Set the Foundation for Future Data Work: We have ambitious plans to leverage data as a key component to our long term product strategy. 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
What they're asking for
- You have Bachelors degree in Math, Science, Engineering, or another data intensive field of study such as Library ScienceEducation
- You have 4+ years of experience working in a Data Science, Data Analytics, or Data Engineering at a high growth startup or scaled technical organizationExperience
- You have experience working with data models, data pipelines and performing analysisSkill
- You have hands on experience working with common data warehouses such as Snowflake, BigQuery, or RedshiftSkill
- Enthusiasm for data modeling; hopefully you have opinions on slow changing dimensionsSkill
- You have a strong understanding of SQL and have used it in complex data environmentsSkill
- You have well-developed opinions on modern data engineering and an ability to bring others up to speedSkill
- You thrive in ambiguity and enjoy tackling complex tasks that have significant impact on the business at largeSkill
- You’re a clear and concise communicator; you enjoy the challenge of explaining complicated ideas in simple terms, both in-person and in writing.Skill
- Experience or exposure with the broader set of technologies in our ecosystem: Google Cloud Platform (BigQuery), Metabase, Terraform, Python, DBT.Skill
Parsed by MeritLog from the employer’s own posting. The full description follows below.
Job description
THE ROLE At Candid Health, we’re searching for an Analytics Engineer to bridge Analytics Engineering, Business Intelligence, and Data Analysis. As a key strategic investment for the company and product, you will be responsible for the data modeling and pipelines that enable our downstream data products. You will work closely with stakeholders across the business and play a foundational role in scaling the data team. Candid Health is positioned to unlock transformative technology for healthcare providers and the BI Engineer will play a critical role in that effort. WHAT YOU’LL DO - Own Data Modeling as a Practice: Build and deliver critical reporting, analytics, and data models for varying use cases. You will be the standardbearer for operational excellence in our efforts to extrapolate data for meaningful outcomes - Set the Foundation for Future Data Work: We have ambitious plans to leverage data as a key component to our long term product strategy. 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 communicator; you enjoy the challenge of explaining complicated ideas in simple terms, both in-person and in writing. - 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. Further note that Candid Health has minimal hierarchy and titles, but has broad ranges of experience represented within roles
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