• Design, develop, and maintain scalable data pipelines to support ingestion, transformation, and delivery into centralized feature stores, model-training workflows, and real-time inference services. • Build and optimize workflows for extracting, storing, and retrieving semantic representations of unstructured data to enable advanced search and retrieval patterns. • Architect and implement lightweight analytics and dashboarding solutions that deliver natural language query experience and AI-backed insights. • Define and execute processes for managing prompt engineering techniques, orchestration flows, and model fine-tuning routines to power conversational interfaces. • Oversee vector data stores and develop efficient indexing methodologies to support retrieval-augmented generation (RAG) workflows. • Partner with data stakeholders to gather requirements for language-model initiatives and translate into scalable solutions. • Create and maintain comprehensive documentation for all data processes, workflows and model deployment routines. • Should be willing to stay informed and learn emerging methodologies in data engineering, MLOps and LLM operations.

• Maintain data environments and processes in Azure and on-premises, ensuring continuous and reliable operation; • Provide advanced administration and support for Databricks (Azure), including troubleshooting and operational tuning; • Monitor and manage pipelines, jobs, integrations, and data routines with a preventive and corrective approach; • Implement fixes and improvements to existing processes, performing root-cause analysis and reducing recurrence; • Lead incident management and resolution (SLA, prioritization, communication, follow-up until stabilization); • Support BI and development teams, ensuring environments are ready for new releases and requests; • Continuously evolve and improve DataOps / CI/CD pipelines for data (governance, quality, and reliability); • Collaborate with infrastructure/architecture teams when needed (capacity, access, security, network, performance); • Ensure adherence to security, governance, and compliance best practices in the data context; • Propose and implement improvements in observability, monitoring, and alerting (metrics, logs, traceability).

Role Description The Data Migration and Platform Support Analyst will support modernization of the Navy’s audit artifact management platform. This role assists with preparation, migration, validation, and organization of data and artifacts as they transition from legacy repositories into a modern enterprise data environment. The analyst will work closely with data platform engineers and functional stakeholders to support data migration activities, validate migrated datasets, and document platform data structures and processes. This position helps ensure data accuracy, traceability, and maintainability as the platform environment evolves. Key Responsibilities - Data Migration & Validation: - Assist with preparation and organization of data and artifacts for migration into the platform environment. - Support migration of datasets from legacy systems such as SharePoint repositories into the modern data platform. - Verify that migrated data is complete, properly structured, and accessible within the platform environment. - Assist platform engineers with data pipeline development and migration activities, including dataset preparation, validation, and testing within the enterprise data environment. - Data Validation & Testing: - Perform validation checks to confirm accuracy and completeness of migrated datasets. - Assist engineers with testing data pipelines and validating dataset outputs. - Document testing results and support issue tracking during migration activities. - Documentation and Process Support: - Document data sources, dataset structures, and migration procedures. - Assist with maintaining platform documentation and operational procedures. - Support development of user reference materials and internal documentation for platform workflows. - Operational Support: - Assist the platform team with organizing datasets and artifact repositories within the platform environment. - Support ongoing data maintenance activities as the platform environment evolves. Qualifications - Bachelor’s degree in Information Systems, Data Management, Business, Computer Science or related field, or equivalent experience. - 1-3 years data management, data migration, or technical program support activities. - Experience with structured data using tools such as Excel, SQL, or similar technologies. - Experience supporting enterprise systems or data environments preferred. Skills - Strong attention to detail when reviewing and validating datasets. - Ability to document technical processes clearly and maintain organized records. - Strong organizational skills managing large collections of data or documents. - Ability to collaborate with engineers and functional teams supporting platform operations. Requirements - Active Secret Clearance. - Contingency – This work is contingent upon award. Salary Range - $65-$90k per year Company Description Montcure, LLC is a Service-Disabled Veteran-Owned Small Business (SDVOSB) founded with a vision to revolutionize consulting and advisory services through innovative, data-driven solutions. The Montcure team recognizes the unique challenges faced by organizations and governments in today’s rapidly evolving business environment. Montcure, LLC is an Equal Opportunity Employer. Montcure, LLC does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.

• Build & Modernize Core Data Infrastructure: Lead the evolution of our existing integrations toward a modern, orchestrated architecture. Design, build, and scale robust data pipelines into a cloud data warehouse, integrating data from our enterprise systems (ERP/EPM/Treasury/HR). • Own the Data Architecture: Set the long-term technical direction for our financial data warehouse and analytics strategy. You'll evolve early pipelines into a scalable, well-modeled platform that serves Finance stakeholders. • Ensure Institutional Data Integrity: Establish rigorous automated reconciliation logic, data quality frameworks, and monitoring within Workato/Tines to ensure all financial, billing, and tax data is 100% accurate, traceable, and SOX-compliant. • Drive Engineering Excellence: Set a high technical bar for the team by introducing data engineering best practices in version control, CI/CD pipelines, error handling, and security standards for financial workflows. • Partner Cross-Functionally: Collaborate deeply with Finance, Accounting, and Strategic Finance stakeholders, alongside Legal, HR, and other core business teams, to translate complex reporting, compliance, and enterprise operational requirements into robust, automated technical solutions across Reddit's broader Corporate Engineering ecosystem.