Data Engineer – MMIS (Medicaid Management Information System)

Job Title: Data Engineer – MMIS (Medicaid Management Information System)

Location: Remote (USA)
Job Type: Contract

Role Overview

We are seeking a highly skilled Data Engineer with mandatory MMIS (Medicaid Management Information System) experience to support large-scale Medicaid data initiatives.

This role focuses on designing, developing, and optimizing scalable data pipelines, ETL processes, and data platforms to support analytics, reporting, and data science use cases within Medicaid programs.

The ideal candidate will have hands-on experience working with Medicaid claims, encounter data, and payer systems, along with strong expertise in SQL, Python, ETL frameworks, and API-based data ingestion.

MUST-HAVE REQUIREMENTS (Non-Negotiable)

• MMIS (Medicaid Management Information System) experience – Mandatory

• Healthcare Payer / Medicaid domain experience

• Strong SQL Proficiency (Advanced – complex queries, optimization, performance tuning)

• Hands-on ETL / Data Transfer experience

• Experience creating and maintaining ETL pipelines

• Experience with API-based data ingestion

• Python for data processing and pipeline development (Pandas, NumPy)

• Experience working with Claims & Encounter Data

• Exposure to CMS guidelines and HIPAA-compliant environments

Key Responsibilities

• Design, build, and maintain scalable and high-performance data pipelines for MMIS systems

• Perform data cleaning, transformation, and validation to ensure high data quality and integrity

• Develop and manage end-to-end ETL pipelines for structured and unstructured healthcare data

• Handle data transfer and ingestion from multiple data sources, including APIs, flat files, and databases

• Process large-scale datasets including claims, encounters, provider, and member data

• Collaborate with Data Scientists, BI teams, and business stakeholders to deliver analytics-ready datasets

• Optimize SQL queries, ETL jobs, and data workflows for performance, scalability, and reliability

• Ensure data integrity, governance, and compliance with CMS and HIPAA standards

• Support regulatory reporting and compliance requirements for federal and state Medicaid programs

• Enable analytics use cases such as Fraud, Waste & Abuse (FWA), cost optimization, and predictive modeling

• Troubleshoot data pipeline failures, production issues, and data discrepancies

• Ensure data sources meet required specifications and business rules

• Translate business requirements into scalable data engineering solutions

Technical Skills

Data Engineering & ETL

• ETL pipeline development, optimization, and maintenance (Critical Skill)

• Data transfer, ingestion, transformation, and validation

• Workflow orchestration and pipeline monitoring

• Data quality checks and governance frameworks

Programming & Querying

• SQL / PL-SQL (Advanced – Mandatory)

• Python (Pandas, NumPy) for data processing and pipeline development

Data Integration

• API-based data ingestion and integration (REST/Batch APIs)

• Experience working with multiple data formats (CSV, JSON, XML, etc.)

Tools & Platforms

• SAS (preferred in Medicaid environments)

• Hadoop / Spark (nice to have)

• BI Tools: Tableau, Power BI

• Cloud Platforms: AWS / Azure / GCP

Healthcare Domain Expertise

• Strong understanding of MMIS systems and Medicaid data models

• Experience with:

  • Claims processing systems

  • Encounter data workflows

  • Provider and member data structures

• Knowledge of CMS reporting standards and compliance requirements

• Exposure to Fraud, Waste & Abuse (FWA) analytics

• Familiarity with payer systems and healthcare data lifecycle

Qualifications

• Bachelor’s or Master’s degree in:

  • Computer Science

  • Data Engineering / Data Science

  • Healthcare Informatics

  • Statistics / Mathematics or related field

• 6+ years of experience in Data Engineering / Analytics Engineering

• Experience handling large, complex healthcare datasets

• Experience working in compliance-driven environments (CMS, HIPAA)

Preferred Qualifications

• Experience in MMIS modernization projects

• Familiarity with healthcare data standards:

  • HIPAA

  • ICD-10

  • CPT

  • HL7 / FHIR (nice to have)

• Experience supporting Data Science / Machine Learning teams

• Experience working in Agile / Scrum environments

Strong communication and stakeholder collaboration skills