Build an AI-Ready Data Foundation (40%) Design and implement curated, semantic data layers (dimensional models, business definitions), ensuring accuracy, traceability, and AI/ML readiness for BI and generative AI use cases
Design scalable SQL-based pipelines to transform raw and enterprise data into analytics-ready assets
Implement data quality frameworks, lineage, and governance, according to standards set by the central data office team
Elevate Analytics & Self-Service (35%) Lead enterprise-grade Power BI semantic model design (Dataflows, composite models, aggregations) to enable low-latency, high-performance reporting for executives and analysts
Integrate and extend enterprise semantic models with AVS-specific business logic and conformed dimensions, aligning definitions across the segment
Define best practices for DAX, M, and workspace governance (deployment pipelines, refresh strategies) within team to advance BI maturity and self-service
Partner with visualization analysts and business leaders to translate requirements into trusted, performant models and reusable domain data products
Drive AI & Advanced Analytics Adoption (25%) Design AI-ready semantic layers and metadata that enable natural-language querying, conversational analytics, automated retrieval, and intelligent workflows
Build and deploy AI solutions using enterprise-approved platforms
Implement operational forecasting, anomaly detection, and segmentation
Engage central AI/ IT for evaluation, architecture guidance and enterprise deployment of AI use cases that exceed approved platform capabilities

Requirements

8+ years in data architecture/engineering delivering dimensional models, curated marts, and production pipelines in cloud environments (e.g., AWS Redshift/S3/Glue, Microsoft Fabric/Azure, ADF or equivalent)
Mastery of SQL, DAX, and Power Query (M); strong performance tuning and model optimization at scale
Deep Power BI experience: semantic modeling, composite models, aggregations, dataflows, and Fabric integration
Hands‑on with Copilot Studio, Fabric Data Agents, or AWS Bedrock
Familiarity with Power Apps / Power Automate for end‑to‑end digital workflows
Preferred Microsoft certifications: DP‑600 (Fabric Analytics Engineer), DP-700 (Fabric Data Engineer), PL‑300 (Power BI Data Analyst), AZ-900 (Azure AI), PL-400 (Power Platform Developer Associate)
AI/ML integration: Python for data prep/modeling; designing data/semantics for NLQ, agentic systems, and platforms such as AWS Bedrock or Fabric ML
Experience partnering with centralized AI and data teams to produce models and agentic solutions
ERP/CRM data integration (e.g., Oracle EBS, Salesforce) and familiarity with enterprise data governance

Benefits

medical
dental
vision
paid time off
a 401(k) plan with employee and company contribution opportunities
life insurance
disability insurance
accident insurance
tuition reimbursement

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data architecturedimensional modelscurated martsproduction pipelinesSQLDAXPower Queryperformance tuningmodel optimizationAI/ML integration

Soft Skills

leadershipcollaborationcommunicationproblem-solvinganalytical thinking

Certifications

DP-600DP-700PL-300AZ-900PL-400