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Read all the information about this opportunity carefully, then use the application button below to send your CV and application. About us: Duet empowers Nurse Practitioners (NP) to tackle the primary care crisis by leading their own practices, closing the gap in access while keeping care local. We're a well-funded seed-stage company led by experienced entrepreneurs and Nurse Practitioners, and backed by investors like Kairos HQ and Lerer Hippeau. We’re building a vertically integrated platform for NP-led practices to thrive as standalone businesses in a time of corporate consolidation. Think of workflows to engage patients, streamline administration, forecast business growth, and drive value-based outcomes while building community among NPs. These solutions sit on a foundation of data that we harness across patients and providers for the benefit of care and practice success. About the role: As an Analytics Engineer at Duet, you will play a key role in shaping how we collect, transform, model, and leverage data to drive clinical and business outcomes. You will work cross-functionally with product, engineering, and clinical teams to build a modern data stack that supports everything from self-serve analytics to predictive modeling. This role blends strategic thinking, technical execution, and a strong sense of ownership — with the opportunity to build foundational systems that scale with our company. Key Responsibilities: Design, implement, and optimize the end-to-end data infrastructure, including ELT pipelines, semantic layers, and analytics-ready datasets to support real-time and batch analytics. Develop and maintain scalable, well-documented data models in our cloud data warehouse to power reporting, analytics, and data science use cases. Partner with stakeholders across operations, product, and care delivery to understand data needs and translate them into robust, intuitive data products. Elevate our analytics capabilities by building trusted dashboards, reporting frameworks, and self-serve tools that enable data-driven decision-making across the organization. Lead data quality initiatives by implementing robust validation and monitoring frameworks to ensure the accuracy, consistency, and integrity of our data. Mentor junior team members and contribute to establishing data best practices, governance standards, and scalable analytics processes. Qualifications: 5+ years of experience in analytics engineering, data engineering, or related roles, preferably in high-growth startups or healthcare environments. Advanced proficiency in SQL and data modeling (e.g., dbt); strong understanding of data warehousing principles and dimensional modeling. Experience with cloud data platforms (e.g., GCP, BigQuery) and modern data stack tools (e.g., dbt) Proficiency with data visualization and BI tools (e.g., Looker, Metabase) and a track record of building high-impact dashboards. Strong communication skills with the ability to partner across technical and non-technical teams, aligning data initiatives with business goals. Familiarity with healthcare data (EHRs, claims, clinical KPIs) is a strong plus. Experience with version control, testing frameworks, and CI/CD pipelines for data is a bonus. Ideal Candidate: Strategic thinker who can translate ambiguous problems into structured data solutions. Passionate about building durable systems that support care delivery and community-building for Nurse Practitioners. Thrives in fast-paced, collaborative environments with a bias toward action and iteration. Committed to data integrity, scalability, and empowering others through high-quality analytics. This role is on-site 3 days a week in New York. Seniority level Seniority levelMid-Senior level Employment type Employment typeFull-time IndustriesHospitals and Health Care Referrals increase your chances of interviewing at Duet by 2x Get notified about new Data Engineer jobs in New York, NY . New York, NY $100,000.00-$200,000.00 1 year ago New York, NY $90,000.00-$140,000.00 11 months ago Want to work with us, but don't see the right job listed? 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