This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Senior Data and Analytics Engineer will own the transformation and semantic layer of the company’s enterprise data platform. This role is responsible for designing, building, and maintaining scalable dimensional models and curated datasets within Snowflake that power financial and operational reporting across all operating companies. This is a hands-on engineering role for someone who lives in SQL and dbt, thinks deeply about data grain and business logic, and takes pride in building clean, reliable reporting infrastructure. The role translates business requirements into well-structured data models and ensures that enterprise metrics are accurate, documented, and trusted. Key Responsibilities - Design and maintain scalable fact and dimension models, define grain, and implement enterprise metric logic using SQL and dbt within Snowflake. - Develop, test, and optimize transformation workflows to ensure clean, reliable, and performant datasets that support financial and operational reporting. - Partner with Finance and Operations to translate business requirements into technical models, ensuring metric definitions are accurate and consistently applied. - Establish validation checks and reconciliation processes to ensure reporting outputs tie to source systems and financial statements. - Publish curated datasets and support dashboards in Sigma or Power BI, enabling self-service analytics while maintaining governance standards. - Work closely with internal or external data engineering resources to define schema expectations, monitor ingestion quality, and resolve upstream data issues. Qualifications - 4+ years of experience in analytics engineering, data engineering, or business intelligence engineering roles - Advanced SQL skills with daily hands-on experience building complex transformations - Strong experience with dbt and modern ELT workflows - Deep understanding of dimensional modeling (fact/dimension design, grain definition, star schemas) - Experience working in Snowflake or similar cloud data warehouse environments - Experience building reporting infrastructure (not primarily ML/data science focused) - Strong understanding of financial and operational reporting concepts - Experience in high-growth, multi-entity, or PE-backed environments preferred Requirements - Writes clean, efficient SQL and builds well-structured, scalable models - Understands data grain, relationships, and how business logic translates into dimensional architecture - Proactively validates outputs and ensures reporting accuracy - Converts operational and financial requirements into precise, reusable technical logic - Takes responsibility for the reliability and integrity of the semantic layer Benefits - Competitive compensation commensurate with experience - Comprehensive benefits package including healthcare - 401(k) match - Flexible time off

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role involves serving as a senior technical leader responsible for shaping and managing the modern data ecosystem. Your contributions will directly impact our mission to enhance healthcare by delivering high-quality data products that support clinical and operational outcomes. - Design and evolve a scalable, secure, cloud-native lakehouse platform leveraging Databricks and Microsoft Fabric. - Define modeling patterns and governance frameworks across the data lifecycle. - Lead design reviews and guide teams in adopting scalable architectures. - Drive long-term platform strategy and evaluate emerging technologies. - Design and implement batch and streaming data pipelines for healthcare data sources. - Develop frameworks for ingestion, quality, lineage, metadata, and observability. - Produce clean, analytics-ready datasets for BI and machine learning. - Implement HIPAA-aligned access patterns and secure handling of PHI. - Architect Databricks workloads for reliability and efficiency. - Integrate Databricks and Microsoft Fabric with Azure services and enterprise systems. Qualifications - Bachelor's degree in Computer Science, Engineering, or a related field. - 7+ years of experience in data engineering. - 2+ years operating in a senior or staff level engineering role. - Proficiency with Databricks, Spark, Delta Lake, dbt, and Python. - Experience designing large-scale cloud data platforms (Azure preferred). - Familiarity with Data Engineering, Data Factory, and Lakehouse. - Advanced expertise in data platform architecture. - Ability to create modular, extensible frameworks for enterprise solutions. - Strong command of distributed data processing techniques. - Experience in HIPAA regulated environments and handling PHI. - Fluency in healthcare data compliance standards. - Technical leadership and mentorship capabilities. - Excellent communication skills with technical and clinical stakeholders. Benefits - 100% remote work (ET or CT work hours preferred). - Collaborative and inclusive work environment. - Opportunities for professional growth and development. - Mission-driven culture focused on improving healthcare. - Diversity, equity, and inclusion in recruitment practices. - Access to cutting-edge technology and resources.

We Breathe Life Into Data At Komodo Health, our mission is to reduce the global burden of disease. And we believe that smarter use of data is essential to this mission. That’s why we built the Healthcare Map — the industry’s largest, most complete, precise view of the U.S. healthcare system — by combining de-identified, real-world patient data with innovative algorithms and decades of clinical experience. The Healthcare Map serves as our foundation for a powerful suite of software applications, helping us answer healthcare’s most complex questions for our partners. Across the healthcare ecosystem, we’re helping our clients unlock critical insights to track detailed patient behaviors and treatment patterns, identify gaps in care, address unmet patient needs, and reduce the global burden of disease. As we pursue these goals, it remains essential to us that we stay grounded in our values: be awesome, seek growth, deliver “wow,” and enjoy the ride. At Komodo, you will be joining a team of ambitious, supportive Dragons with diverse backgrounds but a shared passion to deliver on our mission to reduce the burden of disease — and enjoy the journey along the way. The Opportunity at Komodo Health Quality is at the heart of everything that Komodo Health does, underpinning our vision to reduce the global impact of disease. As Komodo scales its leading Healthcare Map® and AI-driven applications, the need for a unified, measurable standard of trust is paramount. We are not looking for a traditional Staff Data Architect. We are seeking a technical expert with business acumen to bring a clear perspective to guide the definition, creation, and adoption of the future of data quality across Komodo Health, a Staff Data Platform Architect (Reliability & AI Readiness). This role will be a catalyst for enterprise transformation, replacing fragmented quality metrics with a single, implementable standard: Data Reliability. You will be empowered to take the strategic vision of the leadership team, prototype it, advocate for it, and drive its adoption across engineering, product, and data science teams. Looking back on your first 12 months at Komodo Health, you will have accomplished… The Staff Data Platform Architect (Reliability & AI Readiness) will own the execution and organizational adoption of three critical enterprise initiatives: - Redefine the North Star: Lead the conceptual shift from general "data quality" to Data Reliability across the entire organization (is the correct data present at the correct place at the correct time). - Build the Source of Truth: Design, prototype, and champion a single, centralized "Data Reliability Source of Truth" platform to measure and display reliability KPIs at every key stage of the data delivery pipeline. - Automate Frameworks: Create the technical framework and reference architecture necessary to automate the creation, deployment, and monitoring of Data Reliability checks throughout the product development lifecycle. These are the essential job duties you will be responsible for… Strategic Thought Leadership & Conviction (60% Focus: Strategy, Evangelism & Alignment) - Strategic Partnership: Serve as a strategic thought partner to the Head of Data Quality on all matters related to enterprise data reliability and quality assurance architecture. - Vision Execution & Prototyping: Rapidly translate executive vision into tangible prototypes (e.g., proof-of-concept dashboards, reference pipeline code) and scalable technical roadmaps. - Executive Evangelism & Buy-in: Act as the Chief Evangelist for the Data Reliability metric, tirelessly building conviction across executive, product, and engineering leadership, presenting a clear perspective with conviction - Organizational Adoption: Develop and lead change management programs to ensure seamless adoption of the new Data Reliability standard and Source of Truth platform by development teams. - Progress Tracking & Reporting: Define the OKRs and KPIs for the Data Reliability initiative and proactively create and deliver executive-level updates on progress, challenges, and ROI. - Best Practices Evangelist: Formalize, package, and teach "best of the best" architectural and coding approaches for Data Reliability engineering to engineering teams organization-wide. Execution, Architecture & Technical Frameworks (40% Focus: Building & Infrastructure) - Architectural Ownership: Design the end-to-end architecture for the centralized "Data Reliability Source of Truth," ensuring it is highly scalable, performant, and consumable via APIs/dashboards. - Framework Development: Build and implement highly repeatable, configurable technical frameworks (using Python/SQL/Spark) to automate the deployment of Data Reliability checks into CI/CD pipelines and data transformation jobs. - Data Modeling: Drive the modeling and schema design of the core reliability tables, ensuring data from disparate data stages (raw, curated, derived) can be standardized and measured effectively. - AI/ML Alignment: Ensure that the defined Data Reliability metrics are explicitly fit-for-purpose for our AI/ML models, providing the assurance needed for feature engineering and model deployment. - Mentorship & Coaching: Provide technical coaching to existing Data Quality Engineers on advanced techniques required for building enterprise-scale reliability frameworks. What You Bring to Komodo Health The "Evangelist" Mindset & Conviction: - Leadership Presence: Proven ability to create, articulate, and successfully sell a strategic technical vision to senior executive and diverse technical audiences. - High Initiative: Demonstrated history of taking complex, ambiguous problems and independently driving them to concrete, measurable solutions. - Persistence: The mental resilience and conviction necessary to pursue goals despite initial pushback or organizational inertia. Technical Mastery & Strategic Experience: - Experience: 12+ years of cumulative experience in Data Engineering, Data Architecture, or Platform Engineering, with a strong, dedicated focus on enterprise data quality/governance/testing. - Strategic DQM Focus: 5+ years of experience leading or designing enterprise-wide, multi-team data quality frameworks, not just building individual checks. - Technical Deep Dive: Expert-level proficiency in SQL and Python for efficient and complex data manipulation, engineering, and testing. - Platform Expertise: Extensive experience designing and developing with distributed data processing platforms like Spark and pipeline orchestration tools like Airflow. - Data Environments: Deep knowledge of modern cloud data warehousing environments (ideally Snowflake on AWS or similar MPP systems) and robust data modeling practices. - AI Context: Practical experience ensuring data is prepared and validated for AI/ML model consumption. **This is an individual contributor role. #LI-Remote The pay range for each job posting reflects a minimum and maximum range of annual base pay that we reasonably expect to pay for this position within the US. We carefully consider multiple business-related factors when determining compensation, including job-related skills, work experience, geographic work location, relevant training and certifications, business needs and market demands. The starting annual base pay for this role is listed below. This position may be eligible for performance-based bonuses as determined in the Company’s sole discretion and in accordance with a written agreement or plan. This role may also be eligible for equity awards. In addition, this role is eligible for benefits including, but not limited to, comprehensive health, dental, and vision insurance; flexible time off and holidays; 401(k) with company match; disability insurance and life insurance; and leaves of absence in accordance with applicable state and local laws and regulations and company policy. San Francisco Bay Area and New York City: $225,000—$265,000 USD All Other US Locations: $196,000—$230,000 USD Komodo's AI Standard At Komodo, we're not just witnessing the AI revolution – we're leading it. This is a pivotal moment in time, where being first to market with AI transforms industries and sets the bar. We've already established industry leadership in leveraging AI to revolutionize healthcare, and we expect every team member to contribute. AI here isn't optional; it's foundational. We expect you to integrate AI into your daily work – from summarizing documents to automating workflows and uncovering insights. This isn't just about efficiency; it's about making every moment more meaningful, building on trust in AI, and driving our collective success. Join us in shaping the future of healthcare intelligence. Where You’ll Work Komodo Health has a hybrid work model with hubs in San Francisco, New York City, and Chicago. Roles vary — some can be performed from anywhere in the country, others are scoped to a specific region, and some are based near one of our hubs. For hub-based Dragons, we're building intentional in-office rhythms alongside the flexibility that's core to how we work. Whatever your setup, expectations will always be clear before you join. Equal Opportunity Statement Komodo Health provides equal employment opportunities to all applicants and employees. We prohibit discrimination and harassment of any type with regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. By submitting your application, you acknowledge that you have read and understand Komodo Health’s Privacy Notice for Employees and Contractors. This notice explains how we collect, use, and retain applicant data.

• Develop, test, and roll out AI agents in Salesforce to support sales and order processing functions. • Using Boomi, assist in the development of integrations between key business systems. • Data engineering automation: Work with the team to develop a tool that syncs product catalogs and pricebooks between the ERP and CRM. • Support the activities of all IT teams with data engineering expertise.