Senior Data Engineer (Serchhip)

Company DescriptionMobexHealth 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 OverviewMobexHealth 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 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 You’ll Do1. 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 reporting2. 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 outcomes3. 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 deployments4. 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 data5. 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 systemsRequired Qualifications- 10+ years of experience in Data Engineering- Robust 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 KPIsPreferred 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