Scan your resume against ATS criteria for this Databricks Data Engineer SME - Clearance Required role at LMI.
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 (DHA RevOS / 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
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 primary objective is to establish a connected data architecture representing the actual healthcare revenue-cycle workflow:
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 also be responsible for ensuring the resulting Databricks data architecture directly supports
.
In addition, this candidate will have demonstrated experience in collaborating with other data engineers and data scientists, and effective communication with clients.
.
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
architecture for RevOS.
.
supporting operational, financial, revenue-recovery, and executive users.
Build reusable semantic datasets and optimized SQL structures that allow dashboards to consistently calculate RevOS KPIs across enterprise, DHN, MTF, department, provider, encounter, and claim levels.
Ensure dashboard queries and Gold datasets are optimized for performance, refresh cadence, scalability, and concurrent users.
Configure dashboard-level access consistent with Unity Catalog permissions, row-level security, column-level security, PHI/PII requirements, and user roles.
Support dashboard drill-down from summary Healthy / At Risk / Critical indicators into underlying record-level exceptions and work queues.
Profile Government-furnished Bronze datasets and develop source-to-target mappings.
Normalize and conform data from MHS GENESIS Millennium, Abacus, and other approved sources.
Develop reusable Silver-layer entities with common keys, normalized timestamps, enterprise reference dimensions, and standardized business definitions.
Build Gold products supporting:
Revenue-cycle KPIs
Coding-audit financial impact
Charge completeness
Claims readiness
Days-to-Bill
Denial management
Payer performance
Payment/remittance reconciliation
Underpayment detection
AR aging
Revenue recovery
Audit and NFR traceability
Design the data model supporting the
and associated recovery work queues.
Establish entity-resolution methodologies connecting records across disparate source systems.
Develop deterministic and, where appropriate, probabilistic matching for encounters, claims, charges, payments, providers, payers, and related entities.
Develop and maintain
.
Implement automated quality controls addressing completeness, uniqueness, referential integrity, schema conformity, temporal integrity, code validity, financial reconciliation, and source-to-target consistency.
Establish automated Bronze-to-Silver and Silver-to-Gold quality gates.
Build reconciliation controls across billed, allowed, paid, adjusted, patient-responsibility, AR, and recovery values.
Configure and manage
, including catalog/schema/table design, classification, tagging, ownership, lineage, row/column security, and access controls.
Support enterprise metadata federation and DHA data-governance requirements.
Develop scalable Delta Lake structures and optimize partitioning, clustering, SQL performance, storage, and compute usage.
Develop Databricks jobs, workflows, orchestration, production monitoring, alerting, and error-handling processes.
Version-control pipeline code, transformations, data contracts, configurations, and infrastructure-as-code using Government-furnished GitLab.
Support automated CI/CD and controlled production promotion.
Partner with Data Scientists and Analytics Engineers to support predictive modeling, payer analytics, recovery scoring, anomaly detection, and dashboard requirements.
Partner with Revenue Cycle and Coding SMEs to translate hospital revenue-cycle workflows into executable data structures and business rules.
Develop source-to-target documentation, data dictionaries, lineage artifacts, architecture diagrams, runbooks, and sustainment documentation.
Mentor Data Engineers and establish reusable Databricks engineering and visualization patterns across the RevOS environment.
Active SECRET Clearance
Bachelor's Degree and 10+ years of experience in enterprise data engineering, data architecture, data platform development, or related disciplines.
Senior/SME-level hands-on experience with
.
, including Databricks SQL and/or AI/BI dashboards.
Ability to design the underlying Gold/semantic data structures required for enterprise-scale dashboards and operational reporting.
Experience creating and optimizing SQL queries, datasets, and views that support interactive visualization and drill-down.
Strong experience with:
Apache Spark / PySpark
SQL
Python
Delta Lake
ETL / ELT
Data pipeline orchestration
Large-scale data transformation
Demonstrated experience implementing
.
Strong experience designing normalized and analytical data models for complex enterprise environments.
Demonstrated ability to evaluate and
, rather than simply building additional pipelines on top of them.
Experience designing canonical data models, conformed dimensions, enterprise keys, entity resolution, and reusable semantic structures.
Strong knowledge of data-quality engineering, financial reconciliation, metadata, lineage, and data governance.
Experience with Databricks Unity Catalog or equivalent enterprise data-governance/catalog technology.
Experience building production-grade pipelines with automated testing, monitoring, logging, failure handling, and CI/CD.
Ability to translate operational workflows into logical and physical data architectures and visualization-ready products.
Experience supporting highly regulated, healthcare, financial, or Government environments.
Ability to work with PHI, PII, CUI, and other controlled data under applicable security and privacy requirements.
Ability to work across engineering, analytics, visualization, cybersecurity, product, architecture, and business-SME teams.
Ability to meet applicable DHA/DoD security, privacy, access, and data-handling requirements.
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Direct experience developing Databricks data products and dashboards in a DoD enterprise environment.
Experience with DHA, MHS, or other DoD healthcare data.
Experience with MHS GENESIS / Oracle Health/Cerner Millennium and/or Abacus.
Healthcare revenue-cycle data experience involving encounters, coding, charge capture, claims, denials, adjudication, remittance, payments, AR, and revenue recovery.
Familiarity with healthcare EDI transactions including 837, 835, 270/271, 276/277, and 278.
Experience implementing Open Data Contract Standard (ODCS) or comparable machine-readable contracts.
Experience with GitLab-based DevSecOps, infrastructure-as-code, automated testing, and secure promotion.
Familiarity with Collibra or comparable enterprise data catalogs.
Experience supporting financial auditability, reconciliation, lineage, and audit-remediation initiatives.
Familiarity with DoD RMF, NIST, IL4/IL5 environments, and federal data-governance requirements
The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.
US-Remote
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, including Databricks SQL and/or AI/BI dashboards.
.
, rather than simply building additional pipelines on top of them.
.
How to apply for Databricks Data Engineer SME - Clearance Required at LMI?
Click the "Apply on Company Website" button on this page to submit your application directly on the employer's official portal.
What is the salary for this role?
The salary for this role is $123,000 - $160,000 per annum.
What experience is required?
10+ years of experience is required.
Is this position still open?
Yes, currently active and accepting applications.
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