• Design, develop, and optimize database schemas, stored procedures, functions, triggers, and views in SQL Server and other RDBMS platforms. • Provide production database support, including incident response, troubleshooting, root-cause analysis, and resolution of performance and availability issues. • Plan and execute data patching, hotfixes, and schema changes across development, test, and production environments with minimal downtime. • Perform performance tuning, query optimization, indexing strategy, and execution-plan analysis. • Administer database instances: installation, configuration, upgrades, patching, backup and recovery, and disaster recovery planning. • Manage and support databases in cloud environments — Azure SQL Database, Azure SQL Managed Instance, SQL Server on Azure VMs, or equivalent services on other cloud platforms. • Implement and maintain security controls, access management, encryption, and compliance requirements. • Monitor database health, capacity, and resource utilization; set up alerting and proactive maintenance. • Support migrations between on-premises and cloud, and between database versions. • Collaborate with development teams on data modeling, release management, and deployment automation. • Maintain documentation for configurations, procedures, and runbooks.

• Support the development and maintenance of data pipelines, ingestion processes, and data transformations. • Create and maintain SQL queries, Python scripts, and Spark-based workloads used for data processing and analytics. • Assist in troubleshooting pipeline failures, data quality issues, and operational incidents. • Work with senior engineers to implement schema mappings, transformation logic, and data validation rules. • Ensure datasets meet expected schemas, data contracts, and quality standards. • Support metadata management, dataset documentation, and lineage activities. • Assist in maintaining data classification information according to company standards. • Help automate repetitive operational and data management tasks to improve efficiency and reliability. • Contribute to monitoring, alerting, and operational support for data pipelines and workflows. • Participate in testing activities, including unit tests, transformation validation, and data quality checks. • Follow established engineering standards, coding practices, and team development patterns. • Learn and apply security, privacy, and compliance requirements when handling sensitive or regulated data. • Collaborate with Data Governance, Security, and Compliance teams when required. • Contribute to continuous improvement initiatives focused on data trust, reliability, and operational excellence.

• Architect the Data Platform – Own the end-to-end design of our data infrastructure. • Make the foundational calls on pipeline architecture, data modeling patterns, and platform evolution across Snowflake, dbt, Airflow, and Terraform. • Define Engineering Standards – Establish and enforce practices around data quality, testing, observability, and deployment that the rest of the team builds on. • Enable Data-Driven Decisions at Scale – Design semantic layers and data models complex enough to support underwriting, finance, and executive strategy. • Drive Data Governance – Own the governance posture: data contracts, SLAs, lineage, and documentation. • Shape the ML and AI Foundation – Partner with data science and engineering leadership to ensure the platform supports advanced analytics, ML pipelines, and AI initiatives. • Elevate the Team – Mentor engineers, conduct rigorous code and design reviews, and actively close skill gaps. • Partner at the Leadership Level – Engage directly with actuarial, underwriting, finance, and product leaders to translate business complexity into technical roadmap.

About UsHealth is the most important thing in life, and the American healthcare system is completely broken - poor outcomes, high cost, bad patient experience. We're building a new system from the ground up.Our mission is to improve people’s health by making it easy to live a healthy lifestyle. Nourish is the country's largest dietitian-led metabolic health clinic. We’re an AI-native digital health system matching patients with 10,000+ Registered Dietitians, physicians, medications, lab testing, and AI agents to deliver insurance-covered care across all 50 states. Founded four years ago, we've completed millions of appointments, tripled year-over-year, and partnered with health plans covering 200M+ Americans across 250+ health systems. In 2026 we raised a $100M Series C, bringing total funding to $215M. The round was led by Menlo Ventures, with participation from Thrive Capital, Index Ventures, J.P. Morgan Growth Equity Partners, Maverick Ventures, Y Combinator, BoxGroup, Atomico, Daybreak, and Operator Partners. Learn more about our Series C here: Nourish Blog, Bloomberg, Fierce Healthcare, Digital Native, The Pulse Podcast. This is not a job for everyone. We hold an extremely high bar because we believe talent density is our biggest competitive advantage. We're looking for people who actively choose hard, ambiguous problems, who run toward unglamorous work, give and receive candid feedback, and bring relentless resilience without the ego. Our work is important, but we are not self-important. We do this because we’re solving one of the hardest problems in the world, and the problem matters. If that's you, we disproportionately reward it. About the RoleWe are hiring a Senior or Staff Data Engineer to become the first dedicated data engineering hire on Nourish's Data team. This is a high-impact platform role where you'll build the foundation that makes our data faster, more reliable, easier to trust, and more cost efficient as we scale. Our stack includes RudderStack and Fivetran for ingestion, Snowflake as our warehouse, dbt for transformations, and Omni and Metabase for BI. As AI becomes a core way our teams interact with data, you'll also help build the infrastructure, governance, and semantic layer that enable both humans and AI agents to safely and efficiently access trusted data. You'll partner cross functionally to improve the entire data platform - from ingestion and modeling to observability, governance, and production data workflows. This is a full-time role and open to NYC-based candidates (2-3 days/week in office), with exceptional remote candidates considered. Our office is located in Gramercy. Key Responsibilities: - Own and improve data ingestion and orchestration across our modern data stack. - Build a scalable, reliable, and cost-efficient Snowflake platform. - Partner on dbt architecture, testing, CI/CD, and data modeling best practices. - Improve observability, monitoring, and platform reliability. - Build the governance, semantic layer, and self-service capabilities that power trusted analytics and AI. - Help establish production-ready infrastructure for AI and machine learning workloads. - Turn recurring operational pain points into automation, tooling, and reusable platform capabilities. We'd love to hear from you if: - You have 5+ years of experience building modern data platforms or infrastructure. - You've owned production data pipelines and cloud data warehouses. - You're highly proficient in SQL and have experience with Snowflake and dbt (or similar technologies). - You've improved platform reliability, performance, and cost through thoughtful architecture and automation. - You care about building trusted, well-governed data systems that enable self-service analytics. - You're excited about the role AI will play in the modern data platform. - You communicate technical tradeoffs clearly and enjoy enabling other engineers and business teams. More InformationThe Nourish Bar Our Values Why Nourish Exists How We Work Comp Philosophy Benefits Please note that you must be legally authorized to work in the U.S. for this position.