• Maintain a clear view of each team member's delivery commitments, growth plans, and internal contributions. • Develop and grow team members through regular coaching, clear expectations, and constructive feedback. Build a culture of trust, inclusion, and collaboration. • Monitor team health, morale, and workload balance, acting early to address engagement or performance concerns in partnership with practice leadership. • Maintain regular one-to-one connections with each team member, provide clear feedback, and help them remove blockers related to client work, pursuits, or internal initiatives. • Oversee staffing and resource alignment across teams, balancing utilization, development goals, client needs, and sustainable workloads. • Communicate practice priorities and organizational objectives clearly, ensuring teams understand how their work contributes to broader organizational goals. • Define interview standards and mentorship strategies, training others to apply them consistently and improving hiring outcomes and talent growth at scale. • Create and maintain development plans for team members, including stretch assignments, shadowing, certifications, and opportunities for external visibility. • Lead or support performance reviews, promotion recommendations, and compensation input for your teams, using consistent standards that reflect both impact and behavior. • Represent your teams in leadership forums, communicate expectations and decisions clearly back to the group, and bring forward patterns, risks, and successes that should shape practice strategy. • Lead architecture and technical strategy for large Azure programs and portfolios so solutions meet client goals for value, security, scalability, reliability, performance, and cost. • Define modernization blueprints and reference architectures across applications, platforms, and data, including system and subsystem designs, patterns, and standards that simplify delivery and operations over time. • Translate business and product strategy into cloud architecture roadmaps and execution plans that drive measurable outcomes and adapt based on production feedback and telemetry. • Guide major architecture decisions across programs, promote shared design standards and reusable models, and resolve high-impact technical trade-offs. • Work across teams to connect solutions into cohesive end-to-end architectures with clear ownership boundaries and integration contracts. • Provide architectural oversight during delivery through design reviews, forums, and governance, keeping cross-cutting concerns (security, performance, resilience, availability, compliance, observability, and cost) aligned across teams. • Promote modular design, clear boundaries, testability, CI/CD, and observability so non-functional requirements are treated as first-class and systems remain reliable and maintainable. • Use AI tools to accelerate discovery, design, code, tests, documentation, and analysis, and scale successful practices so teams adopt them consistently. • Define and own enterprise data platform strategy centered on Databricks or equivalent lakehouse architectures. • Establish reference architectures spanning ingestion, lakehouse, analytics, and AI/ML. • Set standards and best practices for: Databricks lakehouse design and workload isolation. Delta Lake optimization and data lifecycle management. Streaming and batch processing patterns. Unity Catalog–aligned governance and security models. Guide multi-workspace and multi-region Databricks deployments. • Ensure tight integration between Databricks, Azure-native services, and downstream analytics tools. • Oversee architectural alignment with complementary platforms (e.g., Snowflake, Fabric, Power BI).

• 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.