Analytics Engineer

Rightway•New York, NY

About The Position

We’re hiring an Analytics Engineer to support and scale clinical programs, with a strong focus on building analytics foundations for programs that will be centered around Rightway’s care complete initiatives. This role sits at the intersection of analytics engineering, clinical program management, and business decision-making, and is ideal for someone who enjoys translating complex clinical workflows into clean, usable data models. The ideal candidate will play a pivotal role in developing and maintaining our clinical program data models, onboarding new data sources and optimizing existing data sources and packaging the data in a way that promotes seamless reporting while paving a way for innovation through advanced analytics. This role will involve delivering and analyzing data for various analytics use cases within our Unified Data Warehouse (UDW) and productionalizing AI and ML solutions through the curated data to drive impactful healthcare insights.

Requirements

3 to 4 years working in data analytics and analytics engineering.
Expert-level proficiency in SQL and statistical programming (Python, R).
Expert-level proficiency in DBT (data build tool).
Experience in cloud platforms (preferably in AWS) and hands-on experience in cloud data warehouses (Redshift or Snowflake).
Experience in dimensional modeling and defining star/snowflake schemas to create a foundation for reporting.
Strong business acumen, preferably with exposure to clinical programs, care management, or healthcare operations.
Ability to design data models that reflect real-world clinical workflows, not just technical schemas.
Strong analytical and problem-solving skills.
Ability to understand, tackle, and solve problems from both technical and business perspectives.
Experienced with developing data tools, memos, and presentations to deliver data and insights to stakeholders.

Nice To Haves

Experience operationalizing ML models is a plus.

Responsibilities

Apply hands-on analytics engineering expertise to solve complex, fast paced business and clinical problems using data.
Design, develop and maintain scalable, analytics ready data models and pipelines (primarily in dbt) that power clinical program reporting, metrics and insights in our Unified Data Warehouse (UDW).
Partner closely with clinical program leaders, analysts, product teams, and operations stakeholders to understand program workflows (e.g., enrollment, adherence, outcomes, follow ups) and translate them into intuitive, well documented data models.
Build curated data marts and semantic layers that make analytics for clinical programs (such as diabetes and weight management) easy to self-serve for dashboards, ad-hoc analysis and operational reporting.
Own KPI and metric definitions end-to-end, from raw source data through production-grade models, ensuring consistency, transparency and trust in reporting.
Implement automated data validation, testing and quality checks to ensure high data reliability across clinical and operational datasets.
Continuously optimize data models and warehouse performance for both cost and speed as usage scales.
Contribute to analytics governance by establishing guardrails, documentation and best practices that improve accountability, ownership, and data literacy across teams.
Communicate insights effectively by developing clear data memos, documentation and presentations tailored to clinical and business stakeholders.
Explore and integrate AI-enabled analytics and predictive modeling use cases (e.g., adherence risk, program outcomes, operational forecasting) into the analytics stack. Experience operationalizing ML models is a plus.