> Markdown version of [/jobs/ext/2042904-principal-azure-data-platform-architect-databricks-mlops-lead](https://www.wearedevelopers.com/jobs/ext/2042904-principal-azure-data-platform-architect-databricks-mlops-lead). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Azure Data Platform Architect / Databricks & MLOps Lead - **Company:** UNITECH CONSULTING, L.L.C. - **Location:** Tallahassee, FL, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Microsoft Azure, Batch Processing, Big Data, Cloud Computing, Cloud Computing Security, Cloud Database, Cloud Engineering, Databases, System Configuration, Data Infrastructure, DevOps, Disaster Recovery, Electronic Data Interchange (EDI), Instant Messaging Technology, Python (Programming Language), Machine Learning, Meta-Data Management, Role-Based Access Control, Release Management, Power BI, Azure Data Lake, SQL Databases, Data Streaming, Systems Architecture, Data Logging, File Transfer Protocol (FTP), Enterprise Software Applications, Data Ingestion, Azure Data Factory, System Availability, Delivery Pipeline, Data Layers, Data Lakes, Pyspark, Data Lineage, Machine Learning Operations, Software Version Control, Data Pipelines, Databricks - **Published:** August 13, 2026 - **Apply:** https://www.careerjet.com/jobad/us98bdaf69b3ce8d25d82a1f92ac3b61c4 ## About the Role * Experience Baseline: 10+ years of comprehensive enterprise software or big data engineering experience. * Cloud Depth: 5+ years of dedicated, hands-on Azure cloud architecture and data platform deployment work. * Platform Toolkit: Extensive production-level experience configuring Azure Data Lake Storage Gen2 (ADLS Gen2), Azure Databricks, and Azure Data Factory (or equivalent enterprise orchestration tools). * Languages: Advanced engineering proficiency in Python/PySpark and SQL for streaming and batch processing. * Pipeline Frameworks: Expert knowledge designing Raw, Silver, and Gold data layer architectures, managing schema evolution, data quality validation, and ledger reconciliation scripts. * Ingestion Vectors: Proven success establishing API, database, and flat file-based ingestion pathways across highly disparate legacy architectures. * Cloud Security & Identity: Advanced hands-on mastery of Azure security controls, including Entra ID, role-based access control (RBAC) alignment to least-privilege principles, managed identities, and Key Vault configuration. * DevOps & Monitoring: Strong background building CI/CD deployment pipelines, version-controlled repositories, and production monitoring dashboards. * MLOps Integration: Documented experience supporting machine learning scoring workflows, model deployment automation, or data pipeline drift detection systems. * Government Context: Proven history delivering technology, cloud architecture, or data infrastructure projects for local, state, military, or federal government entities. * Vetting & Location: Must be a U.S.-based citizen or resident. Must be able to successfully clear an FDLE Level II background screening (including fingerprinting) within 5 business days of contract award. Strong Preferences * Direct experience deploying and managing architectures within secure Azure Government cloud environments. * Hands-on configuration experience utilizing MLflow, Delta Lake, or automated data lineage/metadata cataloging repositories. * Background managing technical integrations with Microsoft Power BI workspaces and handling specialized .pbix configuration templates. * Deep technical familiarity with NIST standards (SP 800-53/171), FedRAMP High control baselines, CJIS, or HIPAA data protection guidelines. * Prior experience establishing standardized multi-agency or cross-department state/federal data exchange models. ## Description * Position Type: Part-Time Consultant / Technical Architecture Lead * Target Allocation: 22-26 hours/week average (Note: Workload is highest during the initial architecture build-out, legacy environment integration, automated pipeline deployment, multi-agency onboarding phases, and operational readiness reviews). * Location: Remote (U.S. Based) with periodic travel to Tallahassee, FL as required. * Cold-Start Baseline: The RFQ strictly mandates that all engineering, configuration, and testing occur entirely within State-provided environments. No vendor-hosted development or proprietary runtimes are permitted., This platform will unify statewide oversight, tracking abnormal spending patterns, contract vulnerabilities, and fraud/waste/abuse risks across up to 35 state agencies. Because this is a high-visibility, firm-fixed-price (FFP) state government contract, you will maintain absolute technical accountability for establishing an infrastructure that guarantees a 99% or greater pipeline run success rate and a 99.5% or greater overall system availability rating. Principal Responsibilities * Multi-Environment Architecture Ownership: Take complete engineering ownership of the core system architecture across four distinct, logically isolated State environments: Development (DEV), Test/QA (TEST), User Acceptance Testing (UAT), and Production (PROD). * Cloud Data Foundation Build-Out: Deploy, configure, and manage the State-owned infrastructure utilizing Azure Data Lake Storage Gen2 (ADLS Gen2) and integrated Databricks workspaces. * Analytical Pipeline Orchestration: Establish robust, reproducible patterns for automated data ingestion, incremental/historical loading, canonical schema processing, business rule execution, and machine learning scoring engines. * Automated Reliability Controls: Build and implement data pipeline monitoring to continuously demonstrate a 99% or greater successful run rate, factoring in real-time alerting for data anomalies, pipeline failures, or performance degradations. * Promotion & Release Management: Engineer automated version control, code rollback, environment promotion paths, and disaster recovery mechanics that align strictly with specified Recovery Time Objective (RTO) and Recovery Point Objective (RPO) targets. * Forensic Audit Traceability: Implement exhaustive logging, error handling, retry logic, and metadata management to preserve comprehensive source-to-target data lineage, providing the clear operational evidence required for independent OCIG verification testing. * Technical Agency Onboarding: Coordinate and execute the technical onboarding pipelines for an initial wave of 8-10 state agencies, establishing secure file transfer protocols and resolving cross-system schema differences. * State Ownership Handover: Package and document all system components, mapping templates, code notebooks, and configuration files into a fully editable, non-proprietary State Ownership and Transition Package., * Architecture Scale & Complexity: Specify the exact dataset volumes processed, the number of distinct environments managed, and the precise project duration. * Personal Engineering Contribution: Detail exactly what you personally built, scripted, or configured (e.g., "Coded PySpark reconciliation scripts," "Configured Azure RBAC least-privilege policies"). * System Deployment Status: Explicitly prove that your architectures reached true production, steady-state, or operational status rather than just theoretical design. * Quantifiable Performance Metrics: Provide the precise metrics achieved under your management, such as percentage of pipeline run success rates, system availability uptime, data completeness markers, or page load response times. "We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status" Texting Privacy Policy * Message type: Informational; you will receive text messages regarding your application and potentially regarding interview scheduling. * No mobile information will be shared with third parties/affiliates for marketing/promotional purposes. * Message frequency will vary depending on the application process.Msg & data rates may apply. * OPT out at any time by texting "Stop"., Essential Duties and Responsibilities: - Oversee the automation processes for daily activities, build activities and new feature and functionality with public and private cloud … + 4 days ago + ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Why make use of an integration platform in today's software developments and infrastructure?](https://www.wearedevelopers.com/videos/758-why-make-use-of-an-integration-platform-in-today-s-software-developments-and-infrastructure) ## Related Articles - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)