Principal Data Analyst

Cityblock Health

1d•$110,000 - $145,000

About The Position

Design and build analytic solutions that will inform business decisions, drive operations, measure our performance and demonstrate our value as a company. Serving as a senior individual contributor (IC) technical lead, this role supports the entire Analytics team by establishing analytics best practices, modernizing our data infrastructure, and driving AI-enabled development. This professional acts as a key business and technical partner across Member Outreach, Provider Networks, Gaps in Care, and Clinical Operations stakeholders, ensuring analytic insights and core data architecture are delivered in a way that adds scalable value.

Requirements

Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field (or equivalent practical experience).
7+ years of experience in advanced analytics or analytics engineering, delivering scalable solutions in production data environments.
Deep expertise in dbt, complex SQL, and cloud data warehouses (Google Analytics tech stack: BigQuery, Looker highly preferred).
Hands-on experience building and maintaining enterprise Semantic Layers / Models and metrics frameworks.
Proven fluency with software engineering best practices for data teams, including Git / GitHub version control and CI/CD workflows.
Experience leveraging AI workflows & AI-assisted development tools to optimize code generation, data pipeline building, and documentation.
Demonstrated success acting as an IC technical lead, mentoring analysts, and establishing team-wide analytics standards.

Responsibilities

Establish credibility and trusted working partnerships with clinical, operational and research leaders to identify levers for broad system change, pull them, and measure and communicate the results.
Architect and lead hands-on development of complex, enterprise-grade analytics and reporting solutions supporting the entire Analytics organization.
Implement and configure reporting technologies in the Google tech stack (BigQuery, Looker), as well as advanced dbt data modeling and complex SQL.
Design, standardize, and manage enterprise Semantic Models / Context (e.g., dbt Semantic Layer, Looker LookML) to ensure a single source of truth for metrics across business domains.
Champion and embed AI workflows and AI-enabled development tools (e.g., Copilot, LLM-driven query generation, automated documentation) into the daily analytics lifecycle to accelerate team velocity.
Enforce modern analytics engineering standards, including version control (Git), branch strategies, pull request code reviews, and CI/CD testing frameworks.
Perform complex descriptive analyses over production-scale data sets to drive business decisions. Critically interrogate and interpret data to spot patterns and explain data.
Build-out real-time reporting (both tabular and visual) and work with data tooling across Clinical, Product and Market.
Ensure data quality and validation by building automated dbt testing and data cleansing techniques to correct both ad hoc and systemic issues.
Drive automation capabilities into reporting solutions and data pipelines.
Retain and govern our central analytics dbt repository, semantic definitions, and technical documentation.
Documentation and maintenance of domain-specific analytics roadmaps in partnership with team lead analysts.
Serve as a technical mentor and sounding board for analysts across the department, elevating the team's engineering rigor and modern tooling adoption.
Delivery of analytics supporting broad business needs and achieving a high rate of adoption for data-driven recommendations.