Analytics Engineer creating data products that meet various business needs for the fintech company Stone. Responsible for data pipelines, monitoring, and ensuring data quality.
About the role
- AI Analytics Engineer designing and building analytics solutions for GE HealthCare's AVS segment. Focusing on AI and digital innovation across healthcare data solutions.
Responsibilities
- 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
- 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
- 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
- disability
- accident insurance
- tuition reimbursement
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