Omada Health

• Design, build, and operate scalable Data & AI platform capabilities for analytics, data science, and Generative AI use cases with strong practices around data quality, lineage, observability, security, and governance. • Develop reusable abstractions, templates, services, and workflows that standardize how teams build and manage data pipelines and data products. • Partner with Analytics, Applied-AI, Data-engineering and application teams to deliver platform capabilities that support business and clinical decision-making • Evaluate and integrate modern data and AI technologies with a focus on scalability, reliability, developer experience, and cost efficiency • Apply Generative AI technologies to improve data enablement, documentation, discovery, workflow automation, and platform usability • Promote software engineering best practices, including clean code, automated testing, CI/CD, infrastructure-as-code, monitoring, and secure data handling

• Manage Omada’s HIPAA privacy program, including policy and procedure development, incident investigations, and breach determination and response, ensuring compliance with HIPAA Privacy, Security, and Breach Notification Rules. • Drive privacy-by-design across digital products and services by embedding privacy requirements into product development, engineering workflows, clinical operations, and other business processes. • Execute Omada’s privacy risk assessment program, including data governance, vendor due diligence, and privacy review for commercial deals with employers, health plans, and PBMs, ensuring our contractual and regulatory obligations are met. • Provide expert guidance on consumer privacy compliance, including state consumer health data and general consumer privacy laws, digital advertising, and tracking technologies. • Serve as a key advisor on AI and emerging technologies, including AI privacy guidance and governance considerations across Omada’s AI and machine-learning initiatives. • Support interoperability and health information exchange participation (e.g., Carequality, CommonWell, TEFCA) by counseling on privacy and data use requirements and helping design compliant data flows. • Partner with internal stakeholders on ERISA and self-funded health benefit plan privacy considerations. • Support clinical research privacy compliance and IRB-adjacent work. • Design and deliver privacy training, awareness, and culture-building initiatives that enable Omada teammates to understand and live our privacy obligations in their day-to-day roles.

• Lead research and development of individual- and population-level health trajectory models that predict future member states, risks, and likely progression paths using messy, real-world longitudinal healthcare data. • Produce high-quality experimental evidence and technical recommendations that can lead to tangible product features and have a real impact on individual and population health trajectories. • Lead the design of next-best-action algorithms that convert predicted trajectories into intervention decisions tailored to a member’s current context and likely future path. • Research and apply advanced decision and recommendation policies to safely optimize intervention choice in a healthcare environment. • Define objective functions, reward signals, and policy constraints that balance engagement, clinical effectiveness, fairness, and operational feasibility, partnering with product and clinical teams to ensure outputs are actionable and interpretable. • Serve as the senior scientific lead for algorithmic and evaluation rigor in trajectories and next-best-action, setting standards for problem formulation, evaluation, and publication-quality analysis. • Mentor other scientists and data scientists on advanced methods in temporal modeling, reinforcement learning, and causal inference. • Collaborate closely with platform, MLOps, and product engineering teams to ensure research outputs can be productionized reliably and monitored appropriately.

Role Description We are seeking a highly skilled and motivated Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining robust data architectures and engineering data models and pipelines. This role will play a critical part in ensuring the integrity, scalability, and performance of our data processing and products. - Data Architecture: Design, develop, and implement scalable, secure, and efficient data solutions that meet the needs of the organization. - Data Modeling: Create and maintain logical and physical data models to support business intelligence, analytics, and reporting requirements. - Pipeline Engineering: Design, build, and optimize ETL (Extract, Transform, Load) processes and data pipelines to ensure smooth and efficient data flow from various sources. - Data Integration: Integrate diverse data sources, including APIs, databases, and third-party data, into a unified data platform. - Performance Optimization: Monitor and optimize the performance of data systems and pipelines to ensure low latency and high throughput. - Data Quality and Governance: Implement data quality checks, validation processes, and governance frameworks to ensure the accuracy and reliability of data. - Collaboration: Partner closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet their needs. - Documentation: Maintain comprehensive documentation of data architectures, models, and pipelines for ongoing maintenance and knowledge sharing. - Training: Train and collaborate with teammates effectively in data engineering best practices. - Technical Influence/Leadership: Recommend policy changes and establish department-wide procedures. Use extensive experience and knowledge to resolve complex problems. - Monitor and manage production environment to deliver data within defined SLAs. Qualifications - 5+ years of experience building, maintaining, and orchestrating scalable data pipelines. - 3+ years of experience as a data engineer developing or maintaining integration with software such as Airflow or any Python-based data pipeline codebase. - Experience applying a variety of integration patterns for different use cases. - Experience in backend software development to contribute to distributed computing development and data technologies. - Experience implementing data pipelines and improving the performance of ETL processes and related SQL queries. - Experience in data modeling for OLTP and OLAP applications. - Experience with Cloud platforms such as Amazon AWS. - Familiarity with workflow management tools (Airflow preferred). - Familiarity with cloud-based data warehouses (Amazon Redshift preferred). - Exceptional problem-solving and analytical skills. - Experience working with sensitive data (e.g., PHI / PII) & security best practices. - Familiarity with data governance practices and principles. Requirements - Proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL). - Proficiency in Analytical SQL and experience working with massive parallel processing (MPP) databases (e.g., Redshift, BigQuery, Snowflake). - Proficiency in programming languages such as Python, Java, or Scala. - Knowledge of data modeling techniques (3NF) and tools (e.g., ER/Studio, ERwin). - Software Engineering Mindset: Apply best practices to write elegant, maintainable code and understand automated testing concepts. - Familiarity with business intelligence tools and environments. - Familiarity with big data technologies (e.g., Lambda, Iceberg or Delta Lake, Spark, or Kafka). - Excellent communication and collaboration skills, both written and verbal. - Self-Directed: Leading projects and tasks effectively with cross-functional stakeholders with minimal guidance. Benefits - Competitive salary with generous annual cash bonus. - Equity grants. - Remote first work from home culture. - Flexible Time Off to help you rest, recharge, and connect with loved ones. - Generous parental leave. - Health, dental, and vision insurance (and above market employer contributions). - 401k retirement savings plan. - Lifestyle Spending Account (LSA). - Mental Health Support Solutions. - ...and more!

• Establish and execute a strategic roadmap for Omada's Data Engineering platform. • Lead the delivery of scalable, reliable, and governed data products that enable analytics, reporting, experimentation, and AI-driven insights. • Deliver trusted, reusable production datasets that power Applied Data Science, Product, Clinical, Commercial, Finance, Operations, and Executive analytics. • Lead, develop and grow a high-performing Data Engineering organization through hiring, coaching, mentoring, and career development. • Foster a culture of technical excellence, collaboration, accountability, and continuous learning. • Empower teams to deliver high-impact solutions while maintaining a strong focus on quality and operational excellence. • Partner with Product, Analytics, Data Science, Architecture, Governance, and Engineering leaders to define priorities and accelerate data-driven decision making across Omada. • Translate business needs into scalable platform capabilities and trusted data products. • Build strong relationships across the organization to drive alignment, transparency, and execution. • Establish engineering excellence through improved data quality, reliability, observability, security, and platform performance. • Define and monitor engineering and operational metrics to continuously improve platform health, cost efficiency, and developer productivity. • Guide adoption of Improved reliability, quality, governance, and usability of enterprise data products. • Provide technical leadership for architecture, platform evolution, scalable technologies, reusable frameworks, and engineering standards across Data Engineering. • Expand self-service analytics through trusted and reusable data capabilities. • Influence long-term technology strategy while partnering with engineering leaders across Omada to build a world-class data platform.

Role Description Omada has a dedicated AI Transformation & Enablement organization focused on embedding AI directly into how business functions operate. This team deploys senior engineers directly into functions to partner with teams, understand their workflows, and build production AI systems that drive measurable business impact. Finance is the next major deployment. As the Sr. Forward Deployed Engineer supporting Finance, you will operate as the embedded AI engineering partner for the Finance organization: - Attend planning reviews, close cycles, forecasting discussions, operational reviews, and executive preparation processes. - Understand how Finance operates today and how AI can transform it tomorrow. - Own each agent end-to-end: from discovery and prototyping to shipping, monitoring, and iterating. You will partner closely with the Sr. Director, Strategic Finance, who owns the Finance AI roadmap and business prioritization, while remaining part of Omada’s AI Transformation & Enablement engineering organization. This role is highly cross-functional and combines elements of: - AI engineering - Systems integration - Workflow automation - Product thinking - Business partnership - Organizational enablement You will design, build, deploy, monitor, and continuously improve AI-powered systems that help Finance teams operate more efficiently, improve accuracy and consistency, accelerate decision-making, and scale institutional knowledge. The systems you build will operate within a highly regulated and compliance-sensitive environment that includes SOX, HIPAA, security, and data governance considerations. Qualifications - 5+ years of experience building and deploying software, data, automation, or AI-powered applications. - 2+ years of recent hands-on experience building LLM-based or AI-enabled systems in production environments. - Strong experience designing AI workflows including retrieval systems, orchestration patterns, tool usage, evaluation frameworks, and multi-step reasoning systems. - Strong proficiency in Python and experience building production-quality backend services, APIs, integrations, and automation workflows. - Experience integrating enterprise systems and operational data into AI-enabled workflows. Requirements - Experience working with enterprise business systems such as ERP, planning, financial, or operational platforms. - Experience designing retrieval or contextual knowledge systems across large document and metric corpora. - Familiarity with structured and unstructured enterprise data environments. - Understanding of operational monitoring, evaluation, and observability concepts for AI systems. - Excellent communication and stakeholder management skills. - Proven ability to partner directly with non-technical teams and translate business workflows into scalable technical solutions. - Experience enabling business users through training, documentation, and operational coaching. - Comfortable operating within highly cross-functional and rapidly evolving environments. Benefits - Competitive salary with generous annual cash bonus. - Equity grants. - Remote first work from home culture. - Flexible Time Off to help you rest, recharge, and connect with loved ones. - Generous parental leave. - Health, dental, and vision insurance (and above market employer contributions). - 401k retirement savings plan. - Lifestyle Spending Account (LSA). - Mental Health Support Solutions. - ...and more!

• Drive the execution of GLP-1 solutions within the cardiometabolic platform • Coordinate across product, clinical, data science, engineering, and commercial teams • Lead day-to-day execution of GLP-1 program initiatives • Track and report on program OKRs and KPIs • Develop and manage reporting and dashboards for program performance • Coordinate with clinical, commercial, product, engineering, operations, and regulatory partners

• Lead the design and implementation of backend services and platform capabilities that support large‑scale, data‑rich applications. • Own projects end‑to‑end from technical design through implementation, testing, deployment, and ongoing reliability. • Partner with product, data science, and clinical teams to turn complex requirements into simple, robust solutions. • Design and build scalable backend systems that ingest, process, and serve high‑volume health data. • Lead technical initiatives that improve data reliability, observability, and end‑to‑end system performance. • Drive architecture decisions for integrations with third‑party data sources and APIs. • Improve system resilience and data quality, ensuring correctness in clinically relevant workflows. • Mentor engineers and elevate engineering standards through design reviews, testing practices, and operational excellence. • Contribute to roadmap planning, breaking down ambiguous problems into clear, actionable engineering work.

• Lead strategy across the full cardiometabolic suite including diabetes, hypertension, prediabetes, weight management, cholesterol and GLP-1 programs • Lead a team of 2-3 product marketers and partner across product, clinical and commercial teams • Own positioning, GTM strategy and sales enablement across all stakeholder audiences • Partner with cardiometabolic product and commercial leadership on portfolio strategy and GTM planning • Help shape product and go-to-market road maps based on market gaps and customer needs • Lead packaging and pricing for cardiometabolic products • Own the positioning and messaging across the cardiometabolic suite • Lead end-to-end GTM launches for new cardiometabolic products • Act as the primary product marketing POC for the cardiometabolic suite

• Lead Omada’s Clinical Quality department across program quality, accreditation, safety, health equity, and clinical quality analytics. • Own the operational effectiveness of Omada’s clinical quality infrastructure and the quality performance of core programs, including program-level outcomes. • Define and drive the near-term roadmap for program quality, Clinical Quality & Outcomes Committee (CQOC) priorities, accreditation readiness, quality analytics, and AI bias monitoring. • Translate strategic and emerging priorities into clear quality systems, ownership structures, monitoring standards, and improvement plans. • Serve as the senior leader accountable for the integrity and performance of Omada’s clinical program model across products and care experiences. • Ensure programs are clinically coherent, evidence-based, measurable, aligned to client and member expectations, and improving over time. • Build durable quality infrastructure that goes beyond governance committees and retrospective review to support a growing portfolio of clinical products and care experiences. • Partner closely across Care Delivery, Product, Engineering, Commercial, Compliance, Legal/Regulatory, Data Analytics, and Applied AI leaders to solve cross-functional problems and strengthen Omada’s clinical quality operating system. • Help shape the clinical quality components of Omada’s co-intelligence engine, including the data foundation and knowledge layers needed to better understand member trajectories, behavior change readiness, treatment adherence, biomarker trends, and signals of underperformance. • Advance proactive quality capabilities over time, including predictive risk identification, smarter personalization of interventions, more precise experimentation, and faster scaling of what works. • Oversee clinical quality governance for AI-enabled products, workflows, and decision-support tools, including monitoring for quality, bias, safety, transparency, and performance. • Lead and develop future program-level clinical owners and subject matter experts (SMEs) across cardiometabolic programs including obesity, weight management, GLP-1, diabetes, hypertension, and cholesterol programs. • Represent Omada’s clinical quality strategy and standards with external stakeholders, including clients, employer and health plan partners, accrediting bodies, and other strategic audiences, while helping strengthen market credibility, support commercial conversations, and translate clinical rigor into external trust and growth opportunities.