MAXhealth

Compensation

Full Description

About the position Responsibilities • Monitoring & Incident Management Triage and investigate production incidents, working with ticketing systems (e.g., Fresh Service, ServiceNow, JIRA). Escalate issues as needed and coordinate with analytics, engineering, or business teams for resolution. • Troubleshooting & Root Cause Analysis Use SQL (or other query tools) to dive into data, validate inputs and outputs, and identify data discrepancies. Analyze log files, system alerts, or script execution results to diagnose problems. Propose and implement data fixes or short-term workarounds when necessary. • Support for System Changes and Deployments Participate in deployment activities (especially for data systems), including cutover planning, data migrations, and data model changes. Assist in sandbox or "go-live" support, helping with on-call rotations for after-hours support. • Process Improvement Identify recurring production data issues and propose long-term process improvements. Write or help maintain runbooks and knowledge-base articles for frequently occurring issues. Automate manual checks, alerts, or remediation tasks where possible (using scripting, monitoring tools, etc.). • Collaboration & Communication Liaise with data engineering, data platform, business intelligence (BI), and business stakeholder teams. Provide status updates, incident reports, and postmortem summaries. Train other team members or stakeholders on data issue patterns and resolution strategies. • Documentation Maintain detailed documentation of data processes, workflows, and troubleshooting steps. Keep track of data system architecture, dependencies, and interfaces. Requirements • Bachelor's degree in Information Systems, Computer Science, Data Analytics, or equivalent experience. • 2-5 years of experience in a data support, data operations, or production support role. • Excellent communication and customer-service skills, with the ability to translate technical findings for physicians, senior leaders, and non-technical stakeholders. • Strong SQL skills (T-SQL), including ability to debug procedures, views, and transformations. • Hands-on experience supporting ETL or data integration tools (ADF, SSIS, or similar). • Experience working with healthcare datasets (claims, eligibility, encounters, or payer data). • Strong analytical and problem-solving ability with a high attention to detail. • Familiarity with version control tools (Git DevOps). • Ability to communicate clearly with technical teams and business stakeholders. • Understanding of HIPAA compliance, data privacy requirements, and secure data handling. Nice-to-haves • Experience with Azure Data Factory, Fabric, Databricks, or other cloud data services. • Exposure to HEDIS quality measures or related reporting logic. • Knowledge of Medicare Risk Adjustment workflows, datasets, or HCC/RAF concepts. • Experience supporting BI tools (Power BI, Domo). • Scripting experience (Python, PowerShell) for automation and monitoring enhancements. • Background in managed care, value-based care, or health plan operations.