Senior Analytics/AI Engineer

Responsibilities

• Design and own relational and dimensional (star-schema) data models across development, test, and production tiers.
• Build the transformation, scoring, and derivation logic that turns raw source data into trusted, reconcilable metrics, assessments, and analytics outputs.
• Implement point-in-time and slowly-changing-dimension attribution to ensure historical data rolls up correctly.
• Build and maintain ETL/ELT pipelines and the reference and configuration data behind them, with versioning and effective dating to keep results reproducible.
• Design and tune the analytical store and aggregation strategy for performance, keeping analytics workloads off the transactional systems.
• Implement a scope-based AI query capabilities on Azure OpenAI.
• Implement AI guardrails and deliver predictive and anomaly-detection indicators as governed, explainable analytics.
• Implement data-access controls — row-level and role-based security — aligned to federal security requirements.
• Define and maintain the data contracts and APIs that downstream visualization layers consume.
• Document data models, lineage, model behavior, and as-built records suitable for continuous authorization and customer handoff.

Requirements

• 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.
• Prior experience with a major relational database (Azure SQL or SQL Server), including performance tuning.
• Hands-on experience building LLM-backed capabilities — retrieval-augmented generation (RAG), grounding, prompt design, and model evaluation — ideally with Azure OpenAI.
• Experience with 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.

Preferred Qualifications

• 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).