Candid Health

Engineering

BI(Analytics)Engineer

$135–180k San Francisco, California, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“BI (Analytics) Engineer at Candid Health. Skills: Analytics Engineering, Business Intelligence, Data Analysis, data modeling, pipelines. Build and deliver critical reporting, analytics, and data models for varying use cases. improve and scale our data infrastructure, enabling future ML and AI products”

What You'll Achieve.

enable our downstream data products; play a foundational role in scaling the data team; unlock transformative technology for healthcare providers; extrapolate data for meaningful outcomes; enable future ML and AI products

Industry & Context.

Engineering
Problems you'll solve

tackling complex tasks

What They're Looking For.

Must Have

Bachelors degree in Math, Science, Engineering, or another data intensive field of study such as Library Science, 4+ years of experience working in a Data Science, Data Analytics, or Data Engineering at a high growth startup or scaled technical organization, experience working with data models, data pipelines and performing analysis, hands on experience working with common data warehouses such as Snowflake, BigQuery, or Redshift, understanding of SQL and have used it in complex data environments

Nice to Have

Enthusiasm for data, well-developed opinions on modern data engineering and an ability to bring others up to speed, Experience or exposure with the broader set of technologies in our ecosystem: Google Cloud Platform (BigQuery), Metabase, Terraform, Python, DBT

What You'll Do.

Build and deliver critical reporting

and data models for varying use cases

improve and scale our data infrastructure

enabling future ML and AI products

Deep dive with engineers to understand complex production data

Ensure that tooling and visualization platforms are accurate and available

How You'll Work.

Team & Collaboration

work closely with stakeholders across the business

Communication Scope

clear and concise; explaining complicated ideas in simple terms, both in-person and in writing

Full 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

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