Principal Data Analyst
Cityblock Health · United States
- Hybrid
- Full-time
- $145,000 / year
- United States
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Job highlights
- Lead analytics solutions and AI development.
- Partner with clinical and operational leaders.
- Build enterprise-grade analytics and reporting.
- Standardize semantic models and metrics.
- Mentor analysts and drive adoption.
About the role
About the role
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.
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.
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.
Compensation and Benefits
We take into account an individual’s qualifications, skillset, and experience in determining final salary. This role is eligible for health insurance, life insurance, retirement benefits, participation in the company’s equity program, paid time off, including vacation and sick leave. The actual offer will be at the company’s sole discretion and determined by relevant business considerations, including the final candidate’s qualifications, years of experience, skillset, and geographic location. The expected salary range for this position is: $110,000.00 - $145,000.00 Annual.
Equal Opportunity Employer
Cityblock values diversity as a core tenet of the work we do and the populations we serve. We are an equal opportunity employer, indiscriminate of race, religion, ethnicity, national origin, citizenship, gender, gender identity, sexual orientation, age, veteran status, disability, genetic information, or any other protected characteristic.
We do not accept unsolicited resumes from outside recruiters/placement agencies. Cityblock will not pay fees associated with resumes presented through unsolicited means.
Key skills/competency
- Data Analysis
- Analytics Engineering
- SQL
- dbt
- BigQuery
- Looker
- Data Modeling
- AI Workflows
- Technical Leadership
- Mentorship
Skills & topics
- Data Analyst
- Principal Data Analyst
- Analytics
- Data Science
- SQL
- dbt
- BigQuery
- Looker
- Data Modeling
- Technical Lead
- Healthcare Analytics
- AI
How to get hired
- Tailor your resume: Highlight your experience with dbt, complex SQL, BigQuery, Looker, and AI-enabled development tools, emphasizing your technical leadership and mentorship skills.
- Showcase analytics engineering expertise: Detail your work with version control (Git), CI/CD, and establishing analytics best practices to demonstrate your proficiency in modern software engineering standards.
- Quantify your impact: Provide specific examples of how your analytics solutions informed business decisions, improved operations, or demonstrated company value, using data to illustrate your achievements.
- Prepare for technical and behavioral questions: Be ready to discuss your approach to complex data analysis, semantic modeling, and how you mentor others, reflecting Cityblock's values and collaborative environment.
- Network and research: Understand Cityblock Health's mission and how your role as a Principal Data Analyst contributes to their impact on healthcare.
Technical preparation
Master complex SQL queries and dbt models.,Practice building semantic layers and metrics.,Familiarize with Git and CI/CD workflows.,Experiment with AI coding assistants.
Behavioral questions
Describe a complex data problem you solved.,How do you build trusted stakeholder partnerships?,How do you mentor junior analysts effectively?,How do you ensure data quality and integrity?
Frequently asked questions
- What are the key technical skills required for the Principal Data Analyst role at Cityblock Health?
- The Principal Data Analyst role at Cityblock Health requires deep expertise in dbt, complex SQL, and cloud data warehouses, specifically the Google tech stack (BigQuery, Looker). Hands-on experience with enterprise Semantic Layers/Models and metrics frameworks is crucial. Proficiency in software engineering best practices like Git/GitHub version control and CI/CD workflows, as well as experience leveraging AI workflows and AI-assisted development tools, are also essential.
- How important is experience with AI-enabled development for this Principal Data Analyst position?
- Experience leveraging AI workflows and AI-assisted development tools is highly valued for the Principal Data Analyst position at Cityblock Health. The role involves championing and embedding AI into the daily analytics lifecycle to accelerate team velocity, including using tools for code generation, data pipeline building, and automated documentation. This indicates a focus on modernizing the analytics workflow with cutting-edge technology.
- What does Cityblock Health look for in terms of leadership and mentorship for a Principal Data Analyst?
- Cityblock Health seeks a Principal Data Analyst who can act as a senior individual contributor (IC) technical lead. This includes demonstrated success in mentoring analysts, establishing team-wide analytics standards, and building trusted working partnerships. The ability to elevate the team's engineering rigor and modern tooling adoption is a key leadership expectation.
- Can equivalent practical experience substitute for a Bachelor's degree for the Principal Data Analyst role at Cityblock Health?
- Yes, Cityblock Health states that a Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience, is acceptable for the Principal Data Analyst role. They value a combination of education and hands-on, relevant work experience.
- What is the expected salary range for the Principal Data Analyst position at Cityblock Health?
- The expected salary range for the Principal Data Analyst position at Cityblock Health is $110,000.00 to $145,000.00 annually. The final salary will be determined by individual qualifications, skillset, experience, and geographic location, among other relevant business considerations.
- How does Cityblock Health ensure data quality and consistency in its analytics?
- Cityblock Health ensures data quality and validation by building automated dbt testing and data cleansing techniques. They also focus on designing, standardizing, and managing enterprise Semantic Models/Context (e.g., dbt Semantic Layer, Looker LookML) to establish a single source of truth for metrics across business domains.
- What is the role of a Principal Data Analyst in modernizing data infrastructure at Cityblock Health?
- The Principal Data Analyst at Cityblock Health plays a key role in modernizing data infrastructure by establishing analytics best practices, implementing and configuring reporting technologies in the Google tech stack, and enforcing modern analytics engineering standards like version control and CI/CD. They also architect and lead hands-on development of complex, enterprise-grade analytics solutions.