Data Engineer, AI & Analytics
2 - 5 years
United States
Full-time
Remote
1 month ago
About the role
MobexHealth is seeking a Data Engineer with strong analytics, automation, and data platform experience to help build and scale our end-to-end data ecosystem — transforming activity across our apps, tablets, kiosks, and integrations into actionable insights, automated reporting, and AI-ready data structures.
This role will support the foundation of how MobexHealth measures impact, drives operational decisions, and scales future predictive and AI capabilities across healthcare programs and member engagement platforms.
You will work closely with engineering, product, analytics, and leadership teams to transform fragmented platform data into structured, scalable, and usable intelligence.
What You’ll Do
1. Data Engineering – Build & Support the Data Platform
2. Analytics & Data Insights
3. Reporting, Dashboards & Automation
4. AI & Predictive Data Support
5. Data Quality, Governance & Operations
Required Qualifications
Preferred Qualifications
Additional Requirements
This role will support the foundation of how MobexHealth measures impact, drives operational decisions, and scales future predictive and AI capabilities across healthcare programs and member engagement platforms.
You will work closely with engineering, product, analytics, and leadership teams to transform fragmented platform data into structured, scalable, and usable intelligence.
What You’ll Do
1. Data Engineering – Build & Support the Data Platform
- Help design and maintain scalable cloud-based data platforms and warehouses
- Build ingestion pipelines for:
- Mobile applications
- Tablet and kiosk deployments
- Usage logs and telemetry
- API integrations
- External datasets (claims, eligibility, SDOH, etc.)
- Support event-based data models across multiple products and deployments
- Develop ETL/ELT pipelines for batch and near real-time processing
- Monitor and optimize data platform performance, reliability, and scalability
2. Analytics & Data Insights
- Help translate engagement and operational data into measurable KPIs and insights
- Support implementation of event tracking frameworks across engineering teams
- Build curated datasets and analytical models to support:
- Engagement analytics
- ER diversion and utilization reduction
- Care gap closure
- Behavioral health follow-up (FUH/HEDIS)
- State and health plan reporting
- Partner with Product and Leadership teams to support reporting and analytics initiatives
- Assist in connecting technical data systems with business needs
3. Reporting, Dashboards & Automation
- Build and maintain automated reporting pipelines
- Support development of dashboards and reporting tools for:
- KPI tracking
- Deployment performance
- Cohort analysis
- State and plan comparisons
- Reduce manual reporting through:
- Automated data refresh processes
- Scheduled reports and alerts
- Self-service analytics capabilities
- Support near real-time reporting where appropriate
4. AI & Predictive Data Support
- Structure and prepare datasets for:
- Machine learning workflows
- Predictive analytics initiatives
- Feature engineering
- Support reusable data pipelines for future AI and automation projects
- Assist with:
- Risk stratification models
- Engagement prediction initiatives
- Early intervention analytics
- Work with analytics and AI teams to maintain clean and reliable training datasets
5. Data Quality, Governance & Operations
- Help establish and maintain:
- Data standards
- Naming conventions
- Documentation and lineage
- Support implementation of:
- Data validation checks
- Monitoring and alerting systems
- Automated pipeline testing
- Ensure data integrity, security, and HIPAA-aware practices
- Help support scalable multi-state and multi-client deployments
Required Qualifications
- 3+ years of experience in Data Engineering or Analytics Engineering
- Strong proficiency in Python and SQL
- Experience building ETL/ELT pipelines
- Experience working with cloud platforms (AWS, Azure, or GCP)
- Understanding of:
- Data modeling concepts
- Data warehousing fundamentals
- Structured and event-based data systems
- Experience working cross-functionally with engineering, product, or analytics teams
- Strong analytical and problem-solving skills
Preferred Qualifications
- Experience supporting AI/ML or predictive analytics workflows
- Familiarity with:
- Feature engineering
- Training datasets
- Product analytics or telemetry data
- Experience with BI and dashboarding tools (Tableau, Power BI, Looker, etc.)
- Knowledge of healthcare, Medicaid, or regulated data environments
- Familiarity with streaming or real-time technologies (Kafka, Kinesis, Pub/Sub)
- Experience working in a startup or fast-scaling environment
Additional Requirements
- 3+ years of professional experience in Data Engineering or related roles
- Must be authorized to work in the United States
- No visa sponsorship available
Skills
Information TechnologyTechnology, Information and Internet