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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Analytics/AI Engineer - **Company:** HYERTEK INC. - **Location:** Columbia, MD, United States - **Experience:** Expert - **Salary:** $135,000.0 - $155,000.0 - **Contract:** Permanent contract - **Skills:** .NET Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Microsoft Azure, C Sharp (Programming Language), Cloud Computing, Data Infrastructure, Extract Transform Load (ETL), Data Migration, Data Warehousing, Relational Databases, Document-Oriented Databases, Python (Programming Language), Microsoft Data Access Components, Microsoft SQL Server, SQL Azure, Performance Tuning, Power BI, Service Layer, SQL Databases, Tableau (Software), TypeScript, Management of Software Versions, Azure Data Factory, Large Language Models, Prompt Engineering, Model Validation, Backend, Microsoft Fabric, Front End Software Development, Data Pipelines - **Published:** July 17, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9036120/senior-analyticsai-engineer ## About the Role 7+ years of hands-on data and analytics engineering across data modeling, pipelines, and analytics delivery. Expert SQL, with strong relational and dimensional data modeling. Demonstrated experience building scoring, rules, or calculation logic over data - not just moving data from one place to another. Production experience with a major relational database (Azure SQL or SQL Server), including performance tuning. Proficiency in a backend language for the logic and service layer - strong Python, C#/.NET, or Node.js/TypeScript. Hands-on experience building LLM-backed capabilities - retrieval-augmented generation (RAG), grounding, prompt design, and model evaluation - ideally with Azure OpenAI. Working knowledge of ETL/ELT, data versioning and effective dating, slowly-changing dimensions, and data-access/security design (row-level and role-based). Experience defining data contracts and APIs consumed by separate front-end, reporting, or BI teams. Excellent troubleshooting, documentation, and stakeholder communication skills. Comfort working independently across multiple concurrent engagements. Candidates must have and maintain an active TS/SCI clearance with the Department of Defense., Experience with Azure Government Cloud (IL5/IL6/IL7) and the architectural constraints they impose. Understanding continuous ATO (cATO) / continuous monitoring delivery. Experience securing AI/LLM systems - scope-bound RAG, PII redaction, prompt-injection defense, and data-residency controls in a governed environment. MLOps exposure - feature stores, model evaluation, and de-identified/governed data release. Familiarity with the Microsoft data and analytics ecosystem (Azure data services, Microsoft Fabric) and BI tools (Power BI, Tableau, or comparable), with the judgment to integrate whichever a customer environment requires. ## Description Design and own relational and dimensional (star-schema) data models across development, test, and production tiers, treating the data model as a long-lived, versioned, peer-reviewed deliverable. Build the transformation, scoring, and derivation logic that turns raw source data into trusted, reconcilable metrics, assessments, and analytics outputs - where every figure can be re-derived and verified, never hand-entered. Implement point-in-time and slowly-changing-dimension attribution so historical data rolls up correctly for the period it describes rather than being overwritten by current state. Build and maintain ETL/ELT pipelines and the reference and configuration data behind them, with versioning and effective dating so results stay reproducible over time. Design and tune the analytical store and aggregation strategy for performance, keeping analytics workloads off the transactional systems. Build a scope-based AI query capabilities on Azure OpenAI Implement AI guardrails and deliver predictive and anomaly-detection indicators as governed, explainable analytics - with evaluation and human-review discipline appropriate to a regulated system. Implement data-access controls - row-level and role-based security - aligned to federal security requirements, so analytics and AI honor the same scope model the applications enforce. Define and maintain the data contracts and APIs that downstream visualization layers consume - native front ends, BI tools, or a governed AI layer Partner with security engineers to apply data-protection, de-identification, and governed-release controls; remediate findings and support continuous-monitoring and audit activities. Document data models, lineage, model behavior, and as-built records suitable for continuous authorization and customer handoff. ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Hacking MSSQL on Cloud. All of them. How I became sysadmin on Azure, AWS, GCP and Alibaba.](https://www.wearedevelopers.com/videos/100339-hacking-mssql-on-cloud-all-of-them-how-i-became-sysadmin-on-azure-aws-gcp-and-alibaba) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [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) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)