Data Engineer, Databricks

🕒 Setembro 1

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $123.000 - $160.000 / ano

⏰ Tempo Integral

🟠 Sênior

🔴 Especialista

🚰 Engenheiro de Dados

🦅 Patrocina Visto H1B

Esta empresa já patrocinou vistos H1B no passado.

👻 Score fantasma 17%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

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LMI

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 1961

📦 Logística

🏥 Saúde

🎖️ Defesa

Logistics • Healthcare • Defense

A LMI é uma empresa visionária que se concentra em reinventar o caminho do insight à ação por meio de soluções inovadoras em diversos setores, incluindo IA aplicada e saúde digital. Eles fornecem análises avançadas, suporte de engenharia e otimização de desempenho nos mercados de defesa, saúde e civil, com um forte compromisso em aprimorar a eficácia da missão para clientes governamentais. Com foco na colaboração e pesquisa, a LMI visa promover mudanças positivas por meio de suas diversas capacidades e parcerias.

Descrição

• Lead the technical design and implementation of the RevOS data architecture within Databricks and the DHA War Data Platform • Assess and remediate DHA revenue-cycle data structures, including fragmented schemas, duplicate entities, inconsistent definitions, missing relationships, weak keys, data-quality issues, and reconciliation problems • Develop a canonical revenue-cycle data model connecting patient, encounter, appointment, eligibility, authorization, provider, documentation, diagnosis, procedure, coding, charge, claim, payer, adjudication, payment, denial, AR, appeal, follow-up, and recovery entities • Design and implement Databricks Bronze-to-Silver-to-Gold architecture • Design Gold data products and analytical data marts for dashboards and visualization workloads • Develop and maintain Databricks SQL dashboards, AI/BI dashboards, and native visualizations • Build reusable semantic datasets and optimized SQL structures for RevOS KPI calculations and drill-down analysis • Optimize dashboard queries and Gold datasets for performance, refresh cadence, scalability, and concurrent users • Configure dashboard access using Unity Catalog permissions, row-level security, column-level security, PHI/PII requirements, and user roles • Profile Bronze datasets and develop source-to-target mappings • Normalize and conform data from MHS GENESIS Millennium, Abacus, and other approved sources • Build Gold products supporting revenue-cycle KPIs, coding-audit impact, charge completeness, claims readiness, denial management, payer performance, reconciliation, underpayment detection, AR aging, revenue recovery, and audit traceability • Design the Revenue Opportunity Ledger and recovery work queues • Establish entity-resolution methodologies and deterministic or probabilistic matching across source systems • Develop and maintain ODCS-based machine-readable data contracts • Implement automated quality controls and Bronze-to-Silver/Silver-to-Gold quality gates • Build reconciliation controls across billed, allowed, paid, adjusted, patient-responsibility, AR, and recovery values • Configure and manage Databricks Unity Catalog, metadata federation, lineage, tagging, ownership, and access controls • 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 • Version-control code and infrastructure using Government-furnished GitLab; support CI/CD and controlled production promotion • Partner with Data Scientists, Analytics Engineers, Revenue Cycle SMEs, and Coding SMEs • 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

🎯 Requisitos

• 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 Databricks • Demonstrated experience using Databricks visualization and dashboard capabilities, including Databricks SQL and/or AI/BI dashboards • Ability to design underlying Gold/semantic data structures for enterprise-scale dashboards and operational reporting • Experience creating and optimizing SQL queries, datasets, and views supporting interactive visualization and drill-down • Strong experience with Apache Spark / PySpark, SQL, Python, Delta Lake, ETL / ELT, data pipeline orchestration, and large-scale data transformation • Demonstrated experience implementing Bronze / Silver / Gold medallion architectures • Strong experience designing normalized and analytical data models for complex enterprise environments • Experience evaluating and redesigning or remediating poorly structured existing data environments • 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