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Databricks Data Engineer SME - Clearance Required

Job in Northern, Floyd County, Kentucky, USA
Listing for: LMI Government Consulting
Full Time position
Listed on 2026-09-19
Job specializations:
  • IT/Tech
    Data Engineering
Salary/Wage Range or Industry Benchmark: 123000 - 160000 USD Yearly USD 123000.00 160000.00 YEAR
Job Description & How to Apply Below

Overview

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.

Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

LMI is seeking a skilled Databricks Data Engineer SME (DHARevOS/ Databricks, War Data Platform & Data Visualization) to serve as a senior technical lead responsible for designing, restructuring, and implementing the data foundation required for the Defense Health Agency (DHA) Revenue Cycle Operating System (RevOS).

This role will work directly within a
Databricks-based War Data Platform (WDP) environment
to assess existing DHA revenue-cycle data structures,identify architectural and data-quality deficiencies, and redesign those structures into a scalable, governed, and reusable revenue-cycle data model.

The primaryobjectiveis toestablisha connected data architecturerepresentingthe actual healthcare revenue-cycle workflow:

Scheduling → Eligibility → Registration → Authorization → Patient Care → Documentation → Coding → Charge Capture → Claim → Adjudication → Payment → Denial → Follow-Up → Recovery

The Senior Data Engineer SME will ensure DHA's existing data is reorganized around this workflow so individual encounters, charges, codes, claims, payments, denials, and recovery activities can be connected and traced through the entire revenue lifecycle.

The individual will alsobe responsible forensuring the resulting Databricks data architecture directly supports
production dashboards, operational visualizations,RevOSSITREP views, KPI reporting, and drill-down analysis
.

In addition, this candidate will have demonstrated experience in collaborating with other data engineers and data scientists, and effective communication with clients.

Responsibilities
  • Lead the technical design and implementation of theRevOSdata architecture within
    Databricks and the DHA War Data Platform
    .
  • Assess and remediate DHA's existing revenue-cycle data structures, including fragmented schemas, duplicate entities, inconsistent definitions, missing relationships, weak keys, data-quality issues, reconciliation problems, and structures that do not align to the operational workflow.
  • Develop a target-state canonical revenue-cycle data model connecting beneficiary/patient, encounter, appointment, eligibility, authorization, provider, MTF, documentation, diagnosis, procedure, coding, charge, claim, claim line, payer,adjudication, remittance, payment, adjustment, denial, AR, appeal, follow-up, and recovery opportunity.
  • Design and implement the Databricks
    Bronze → Silver → Gold
    architecture forRevOS.
  • Design Gold data products and analytical data marts specificallyoptimizedto support
    Databricks dashboards and visualization workloads
    .
  • Develop and maintain
    Databricks SQL dashboards, AI/BI dashboards, and native visualization capabilities
    supporting operational, financial, revenue-recovery, and executive users.
  • Build reusable semantic datasets and optimized SQL structures that allow dashboards to consistently calculate

    RevOSKPIs across enterprise, DHN, MTF, department, provider, encounter, and claim levels.
  • Ensure dashboard queries and Gold datasets areoptimizedfor performance, refresh cadence,…
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