Senior Data Engineer

Company Description MobexHealth is a leader in technology-enabled healthcare solutions focused on delivering whole-person virtual care and advancing health equity. With configurable solutions that include mobile devices, intuitive apps, automated processes, and seamless integrations, MobexHealth ensures a streamlined experience for clients. The company is committed to revolutionizing healthcare through innovative digital solutions, enabling better care delivery for diverse communities. Join MobexHealth to be a part of transforming the future of healthcare.

Role Overview MobexHealth is seeking a

Senior Data Engineer

to design and build the data architecture that transforms activity across our apps, tablets, kiosks, and integrations into actionable reporting, dashboards, and AI-ready datasets. This role will create the backbone of our data lake, reporting pipelines, and analytics structure — helping us answer critical questions such as: How are members engaging across deployments? What actions correlate with reduced ER utilization? Where are care gaps closing? Which populations are at highest risk? How do state deployments compare? You will turn raw platform data into structured insight that powers product decisions, client reporting, executive dashboards, and predictive initiatives.

What You’ll Do 1. Build & Own the Data Lake Architecture Design and implement a scalable cloud-based data lake Ingest data from: Mobile applications Tablet/kiosk deployments Usage logs and telemetry API integrations External data feeds (claims, eligibility, etc.) Standardize and structure event data across products Develop clear schemas and data models for cross-platform reporting 2. Make Platform Data Actionable Transform raw engagement data into meaningful metrics Define event tracking standards across engineering teams Build curated datasets to support: Engagement reporting ER diversion impact measurement Care gap closure tracking Behavioral health follow-up reporting Deployment comparisons across states and MCOs Partner with Product to ensure instrumentation supports measurable outcomes 3. Reporting & Analytics Infrastructure Build reporting pipelines for internal and client-facing dashboards Design executive-level data views (multi-state rollups, cohort comparisons, KPI tracking) Enable real-time and near-real-time insights where needed Optimize performance and scalability for growing deployments 4. Enable AI & Predictive Capabilities Structure datasets for ML model training and feature engineering Build reusable feature pipelines Support risk stratification and predictive engagement models Partner with AI initiatives to ensure clean, reliable input data 5. Governance & Data Structure Establish clear data documentation and lineage Create naming conventions and data standards Implement monitoring, validation, and automated pipeline testing Ensure reliability, integrity, and scalability of data systems

Required Qualifications 10+ years of experience in Data Engineering Strong proficiency in

Python and SQL Experience building scalable ETL/ELT pipelines Experience designing and maintaining

data lakes or modern cloud data warehouses Deep understanding of data modeling (event-based modeling, dimensional modeling) Experience with AWS, Azure, or GCP Experience working with product and engineering teams to define instrumentation Strong analytical thinking and ability to translate product activity into measurable KPIs

Preferred Qualifications Experience working with mobile app telemetry or product analytics data Experience building engagement or utilization dashboards Familiarity with healthcare, Medicaid, or regulated environments Experience with streaming/event pipelines (Kafka, Kinesis, Pub/Sub) Exposure to ML/AI data pipelines Experience in a startup or scaling technology company