Data Platform Lead

Job ID: 9552
Job Type: Contract To Hire
Salary Range: $200k - $225K
McLean, Virginia, US
Referral Bonus: +/- $1664
Posted:

To Apply for this Job Click Here

Job Title: Data Platform Lead (RCM Platform)
Location: Remote (U.S.)
Job-Type: Consulting / Contract

Employment Eligibility: Gravity cannot transfer nor sponsor a work visa for this position. Applicants must be eligible to work in the U.S. for any employer directly (we are not open to contract or “corp to corp” agreements).
Role Overview:
Our client is seeking a Data Engineer to support the design, development, and deployment of data pipelines and data services across a Revenue Cycle Management (RCM) platform. This role focuses on building scalable, production-grade data systems that power AI-enabled workflows across claims, denials, AR management, coding, and performance analytics.

The role includes designing and managing cloud-native data platforms, data lakes/fabrics, and pipeline orchestration, supporting both analytics and AI use cases.
Responsibilities:

  • Design and build scalable data pipelines for RCM use cases
  • Develop ingestion frameworks for structured and unstructured data (claims, remits, account notes)
  • Implement ETL/ELT pipelines and data transformation logic
  • Build and maintain enterprise data lake/data fabric architectures
  • Integrate data across enterprise systems and APIs
  • Ensure data quality, lineage, and governance
  • Support data services for AI/ML and analytics workflows
  • Deploy and manage data workloads in cloud environments using modern DevOps practices

Requirements:

  • Minimum of seven (7)+ years of overall work experience
  • Experience building and deploying data pipelines and data platforms in production
  • Strong SQL and Python skills
  • Experience with cloud data platforms (Azure, AWS, or GCP)
  • Experience with ETL/ELT and large-scale data processing
  • Understanding of data modeling, data quality, and governance
  • Experience integrating enterprise data sources and APIs
  • Experience with data engineering frameworks
  • Experience with data pipelines (ETL/ELT) and large-scale data processing
  • Experience with cloud data platforms (Azure Data Factory, AWS, GCP)
  • Experience with data lake / data fabric architectures
  • Experience with structured and unstructured data integration
  • Experience with API integration and data ingestion patterns
  • Experience with data quality, governance, and lineage
  • Experience with CI/CD and DevOps for data pipelines
  • Experience with distributed processing (Spark or equivalent)
  • Experience delivering production data systems at scale

Preferred Qualifications:

  • Experience in healthcare RCM data (claims, billing, AR)
  • Experience supporting AI/ML or analytics platforms
  • Familiarity with data lakehouse architectures
  • Experience with orchestration tools (Airflow, Azure Data Factory, etc.)
  • Experience working in regulated environments

Job Title: Data Platform Lead (RCM Platform)
Location: Remote (U.S.)
Job-Type: Consulting / Contract

Employment Eligibility: Gravity cannot transfer nor sponsor a work visa for this position. Applicants must be eligible to work in the U.S. for any employer directly (we are not open to contract or “corp to corp” agreements).
Role Overview:
Our client is seeking a Data Engineer to support the design, development, and deployment of data pipelines and data services across a Revenue Cycle Management (RCM) platform. This role focuses on building scalable, production-grade data systems that power AI-enabled workflows across claims, denials, AR management, coding, and performance analytics.

The role includes designing and managing cloud-native data platforms, data lakes/fabrics, and pipeline orchestration, supporting both analytics and AI use cases.
Responsibilities:

  • Design and build scalable data pipelines for RCM use cases
  • Develop ingestion frameworks for structured and unstructured data (claims, remits, account notes)
  • Implement ETL/ELT pipelines and data transformation logic
  • Build and maintain enterprise data lake/data fabric architectures
  • Integrate data across enterprise systems and APIs
  • Ensure data quality, lineage, and governance
  • Support data services for AI/ML and analytics workflows
  • Deploy and manage data workloads in cloud environments using modern DevOps practices

Requirements:

  • Minimum of seven (7)+ years of overall work experience
  • Experience building and deploying data pipelines and data platforms in production
  • Strong SQL and Python skills
  • Experience with cloud data platforms (Azure, AWS, or GCP)
  • Experience with ETL/ELT and large-scale data processing
  • Understanding of data modeling, data quality, and governance
  • Experience integrating enterprise data sources and APIs
  • Experience with data engineering frameworks
  • Experience with data pipelines (ETL/ELT) and large-scale data processing
  • Experience with cloud data platforms (Azure Data Factory, AWS, GCP)
  • Experience with data lake / data fabric architectures
  • Experience with structured and unstructured data integration
  • Experience with API integration and data ingestion patterns
  • Experience with data quality, governance, and lineage
  • Experience with CI/CD and DevOps for data pipelines
  • Experience with distributed processing (Spark or equivalent)
  • Experience delivering production data systems at scale

Preferred Qualifications:

  • Experience in healthcare RCM data (claims, billing, AR)
  • Experience supporting AI/ML or analytics platforms
  • Familiarity with data lakehouse architectures
  • Experience with orchestration tools (Airflow, Azure Data Factory, etc.)
  • Experience working in regulated environments

To Apply for this Job Click Here

Equal Employment Opportunity Statement
Gravity IT Resources is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other legally protected characteristic. All employment decisions are based on qualifications, merit, and business needs.

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